Mechanisms of Resistance

Penicillin-Binding Protein Typing, Antibiotic Resistance Gene Identification, and Molecular Phylogenetic Analysis of Meropenem-Resistant Streptococcus pneumoniae Serotype 19A-CC3111 Strains in Japan

Satoshi Nakano, Takao Fujisawa, Yutaka Ito, Bin Chang, Yasufumi Matsumura, Masaki Yamamoto, Shigeru Suga, Makoto Ohnishi, Miki Nagao
DOI: 10.1128/AAC.00711-19

ABSTRACT

Since the introduction of pneumococcal conjugate vaccines, the prevalence of non-meropenem-susceptible pneumococci has been increasing in Japan. In an earlier study, we demonstrated that multidrug-resistant serotype 15A-ST63 in Japan has a specific pbp1a sequence (pbp1a-13) that could promote meropenem resistance. To trace the origin of pbp1a, we analyzed isolates of serotype 19A-CC3111, which is the most prevalent non-meropenem-susceptible clone in Japan. We analyzed a total of 119 serotype 19A-CC3111 strains recovered in Japan using whole-genome sequencing. Of the 119 isolates, 53 (44.5%) harbored pbp1a-13, indicating that the clone may be the primary reservoir of the pbp1a type and that the pbp1a region may be horizontally transferred between different serotype strains. The single acquisition of pbp1a-13 seemed to cause only penicillin resistance and not multidrug resistance; a combination of penicillin-binding protein (PBP) recombination in the pbp2b and/or pbp2x region(s) with acquisition of pbp1a-13 caused multidrug resistance. Conserved amino acid motif analysis suggested that the pbp1a 370SXXK, pbp2b 448SXN, and pbp2x 337SXXN motifs were the candidates for amino acid substitutions increasing the MICs of meropenem, cefotaxime, and penicillin. We identified a specific clone that was correlated with multidrug resistance, although no correlation was observed between phylogenetic trees generated using core genomes and those generated with only the cps locus. All tested isolates were highly erythromycin resistant, and most harbored mefE within macrolide efflux genetic assembly (MEGA) elements and ermB within Tn917, which was inserted within Tn916 and exhibited a structure identical to that of Tn2017.

INTRODUCTION

Streptococcus pneumoniae is a common pathogen that causes bacterial infections such as pneumonia, otitis media, occult bacteremia, and meningitis (1). Pneumococci are typically surrounded by a polysaccharide capsule that can be used to classify strains into serotypes (2). To prevent pneumococcal infectious diseases, 7-, 10-, and 13-valent pneumococcal conjugate vaccines (PCVs) that target a subset of the serotypes have been introduced in many countries (2). According to previous studies, the total number of invasive pneumococcal disease (IPD) cases decreased dramatically after the introduction of PCVs (3–7). However, an increase in the rate of identification of non-PCV serotype pneumococci was also observed after their introduction (4, 8–10).

PCV7 was licensed in Japan in February 2010 and was used on a voluntary basis until April 2013. During this period, the estimated rates of PCV7 vaccination in children under 5 years of age increased from <10% in 2010 to 80% to 90% in 2012. In April 2013, PCV7 was approved as a routine vaccination in Japan, and the vaccine was switched to PCV13 in October 2013. We conducted a nationwide pediatric pneumococcal infection surveillance study in Japan during the PCV13 era between 2012 and 2014 (8). In that study, we demonstrated an increase in meropenem (MEM)-resistant pneumococci; most of the meropenem-resistant isolates belonged to one of serotypes 15A, 19A, and 35B, with few exceptions.

According to previous studies, amino acid substitutions in the proteins encoded by pbp1a, pbp2b, and pbp2x, especially in their transpeptidase domains, are the primary causes of penicillin resistance (PC-R) and cephalosporin resistance (including carbapenem resistance) (11). Therefore, the penicillin-binding protein (PBP) profile of an isolate based on the pbp1a, pbp2b, and pbp2x sequences can predict its resistance, and a database of PBP types is published by the Centers for Disease Control and Prevention (CDC) and is available on their website (https://www.cdc.gov/streplab/pneumococcus/mic.html) (9, 12, 13).

In a previous study, using this PBP profile, we demonstrated that non-meropenem-susceptible serotype 15A-ST63 strains in Japan harbored type 13 pbp1a (pbp1a-13), which can promote meropenem resistance. Although pbp1a-13 was primarily identified in serotype 19A-ST320 strains that were prevalent in the United States after the introduction of PCV13 (9), this clone has not been prevalent in Japan. Thus, the origin of the pbp1a type and its prevalence in other serotypes, such as 19A and 35B, which were the dominant serotypes of meropenem-resistant pneumococci, are still unknown. Considering that the number of serotype 15A isolates with pbp1a-13 has been increasing since the introduction of PCV13 in 2013 in Japan, we anticipated that there would be a dominant reservoir clone with pbp1a-13 that transmitted the allele to serotype 15A strains in Japan. Thus, we performed whole-genome sequencing of serotype 19A-CC3111 isolates from Japan belonging to the most prevalent clone in Japan after the introduction of PCV7 to elucidate the PBP profile of the isolates.

RESULTS

Whole-genome sequencing statistics.The sequencing statistics are shown in Table S2 in Text S1 in the supplemental material. The average numbers of contigs and N50 (bp) of isolates analyzed in this study were 67.4 (standard deviation [SD], ±6.87) and 57,118 (SD, ±6,694), respectively.

Profile of antimicrobial resistance genes and pilus type.Throughout the surveillance study, we collected a total of 101 MEM-S and 18 MEM-IR serotype 19A-CC3111 isolates (see Table S1 in Text S1). Of the 119 serotype 19A isolates, 114 isolates were ST3111, and the other 5 isolates were one-allele variants of ST3111. The typical profile of resistance genes and pilus type of the 119 isolates was positive for ermB, tetM, mefE, and pili1 and negative for ermTR, tetO, and folA substitutions, folP insertions, and pili2, with a few exceptions (see Table S3 in Text S1).

Correlation between the antimicrobial susceptibility and PBP profiles.The most prevalent PBP profile was pbp1a:pbp2b:pbp2x = 13:24:112 (n = 47), followed by 2:0:112 (n = 29) and JP2:16:112 (n = 22) (Table 1; see also Table S1 and Table S4 to S6 in Text S1). We identified 53 isolates with pbp1a-13 in non-meropenem-susceptible serotype 15A-ST63 isolates in Japan in our previous study (14). Among the 53 isolates, 51, 20, 1, and 17 showed penicillin-G resistance (PCG-R), cefotaxime intermediate resistance (CTX-IR), CTX-R, and meropenem intermediate resistance (MEM-IR), respectively. In addition, we identified 14 isolates that were multiply beta-lactam resistant (PCG-R, CTX-IR or CTX-R, and MEM-IR or MEM-R), and 13 of the 14 isolates had a PBP profile of pbp1a:pbp2b:pbp2x = 13:24:112.

View this table:
TABLE 1

PBP profile and antimicrobial susceptibilitiesa

Conserved amino acid motifs.Details of the correlations between antimicrobial susceptibilities and amino acid motifs are provided in Table 2 (see also Data Set S1 in the supplemental material). With regard to the pbp1a 370SXXK motif, all 35 isolates with 370STMK were PCG-S, CTX-S, and MEM-S, except for 1 isolate that was CTX-IR. Of the 75 isolates with pbp1a SSMK, 73 (97.3%), 23 (30.7%), and 18 (24.0%) were PCG-R, CTX-IR or CTX-R, and MEM-IR, respectively. Of the nine isolates with pbp1a SAMK, six (66.7%), eight (88.9%), and zero (0%) were PCG-R, CTX-IR or CTX-R, and MEM-IR, respectively. With regard to the pbp2b 448SXN motif, we identified two types of motifs, 448SSNT (n = 47) and 448SSNA (n = 72). Most isolates (113/119) had the pbp2x 337SAMK motif, and the isolates had a broad range of susceptibilities to penicillin (PC), cefotaxime (CTX), and meropenem. All 119 serotype 19A isolates had the same motifs of pbp1a 466SSN and 557KTG, pbp2b 391SVVK and 620KTG, and pbp2x 395SSN and 547KSG, according to R6 PBP coordination (GenBank accession no. NC_003098.1).

View this table:
TABLE 2

Antimicrobial susceptibility and amino acid motifs of pbp1a, pbp2b, and pbp2xa

Phylogenomic analysis.Phylogenomic analysis suggested the existence of four resistance-associated clusters (clusters 1, 2, 3, and 4) among serotype 19A-CC3111 isolates in Japan (Fig. 1; see also Fig. S1 in Text S1 in the supplemental material). Cluster 4 was the most likely to be resistant to penicillin, cefotaxime, and meropenem.

FIG 1
FIG 1

Phylogenetic tree, susceptibility to penicillin, cefotaxime, and meropenem, and PBP profiles for all serotype 19A-CC3111 isolates collected in Japan between 2012 and 2014. The phylogenetic tree was created based on core-genome methodology using RAxML.

All 18 MEM-IR isolates except for 1 were included in cluster 4, for which most isolates (16/17 isolates) had a PBP profile of pbp1a:pbp2b:pbp2x = 13:24:112. Clusters 1 to 3 comprised isolates with low resistance to meropenem (MIC ≥ 0.12 mg/liter) exclusively, all of which had PBP profiles of pbp1a:pbp2b:pbp2x = JP2:16:112. Clusters 1 to 4 were also resistant to penicillin; most (30/40) of the PCG-R isolates were included in cluster 1, 2, 3, or 4. Conversely, 18/62 isolates with low cefotaxime susceptibility (MIC = 0.5 mg/liter) and 12/32 CTX-IR and -R isolates were distributed outside clusters 1 to 4.

Divergence time estimation.The phylogenetic tree generated using BEAST showed a cluster 4-specific clade that included all isolates in cluster 4 of the core genome-based phylogenomic tree (see Fig. S2 in Text S1). The divergence time when the resistant cluster branched was predicted to be approximately 1965.4, with 95% of the highest posterior density (HPD) occurring between 1882.3 and 2002.2, before the introduction of PCV7 in Japan.

Erythromycin resistance and Tn916-like integrative conjugative element content.All serotype 19A-CC3111 isolates tested in this study were highly resistant to erythromycin, with an MIC of 128 mg/liter (n = 2) or >128 mg/liter (n = 117), and had Tn916-like integrative conjugative elements (ICE). The structure of the Tn916-like ICE identified in this study is summarized in Fig. 2. For 110 of the 119 isolates, a macrolide efflux genetic assembly (MEGA) (15, 16) element that carries mefE was inserted within ORF6 of Tn916, and Tn917, which carries ermB, was also inserted within ORF9 of Tn916. The structure of this Tn916-like ICE was identical to that of Tn2017 (17). In 8 of the other 9 isolates, complete sequences of MEGA and Tn917 were identified, although the structures of the surrounding regions were not determined because of the short lengths of the contigs. In one isolate, ermB was inserted between ORF19 and ORF20 of Tn916, and mefE was not identified, which was identical to the characteristics of Tn6002 (18), which was widely observed in serotype 15A-ST63 isolates in Japan (19). In eight isolates, a complete Tn916-like element was not extracted because of the short length of the corresponding contig.

FIG 2
FIG 2

Comparisons of the Tn916-like integrative conjugative element (ICE) of serotype 19A-CC3111 isolates. Red bands between the sequences indicate BLASTN matches. In Tn2017, a macrolide efflux genetic assembly (MEGA) that contained mefE was inserted between ORF6 and ORF9 of Tn916, and Tn917, which contains ermB, was inserted within ORF9 of Tn916. In Tn6002, ermB was inserted between ORF19 and ORF20 of Tn916, and mefE was not identified. The reference sequence of Tn916 was submitted as NCBI reference sequence CR931676.1.

Variation of the serotype 19A cps loci.A phylogenomic tree created using the cps locus did not generate clusters similar to those generated by the core genome-based phylogenomic analysis (clusters 1 to 4) (see Fig. S3 in Text S1).

DISCUSSION

In this study, we showed the molecular background of serotype 19A-CC3111 strains collected in Japan in the PCV7 to PCV13 era. The 19A-ST3111 clone was the most prevalent clone in Japan according to the results of previous pediatric nationwide IPD and non-IPD surveillance during the era of PCV7 and PCV13 in Japan. However, according to the multilocus sequence type (MLST) database, ST3111 has been identified only in Japan, except for two isolates (submitted from the United States in 1989 and from China in 2011). Considering that ST3111 did not have any alleles in common with ST199 and ST320, which represent sequence types in serotype 19A that have been prevalent after the introduction of PCV7, this clone should be highly specific to Japan. In Japan, the number of cases attributable to non-meropenem-susceptible serotype 15A-ST63 pneumococci increased after the introduction of PCV7 and PCV13 (8, 20). A previous study demonstrated that this resistance was caused by recombination in the pbp1a region, which resulted in the insertion of pbp1a-13 (20). This pbp1a-13 allele was identified in serotype 19A-ST320 isolates in the United States (9); however, this clone was not prevalent in Japan. In this study, we showed that pbp1a-13 was prevalent in Japan in serotype 19A-CC3111 isolates, which was the most prevalent clone in the post-PCV7 era; of the 119 serotype 19A-CC3111 isolates tested in this study, 53 (44.5%) had pbp1a-13. This result suggests that the serotype 19A-CC3111 clone is one of the reservoirs of pbp1a-13. Among serotype 19A-CC3111 isolates in Japan, the most prevalent antimicrobial susceptibility pattern was PCG-S, CTX-S, and MEM-S (34/119 isolates). Of these 34 isolates, 29 had the common PBP profile pbp1a:pbp2b:pbp2x = 2:0:112, which seemed to be an ancestral PBP profile. We analyzed only one isolate that had an alteration within the pbp1a region, resulting in the PBP profile pbp1a:pbp2b:pbp2x = 13:0:112, and it did not show an increase in meropenem MIC, suggesting that alteration of only pbp1a does not strongly affect meropenem resistance. However, the isolate displayed increased resistance to penicillin and cefotaxime. This result implies that the acquisition of pbp1a-13 caused an increase in the MIC of penicillin and cefotaxime by itself and that the combination of that alteration with other PBPs (pbp2b and/or pbp2x) caused meropenem resistance. Interestingly, all 49 isolates with pbp1a-13 and pbp2x-112 and without pbp2b-0 showed an increase in the meropenem MIC. In the U.S. original PBP profile database, 21 PBP sets with pbp1a-13 corresponding to penicillin susceptibility and 19 sets corresponding to meropenem susceptibility have been submitted (21). According to this database, 7 of the 21 sets were submitted as highly penicillin-resistant strains (MIC ≥ 8 mg/liter), whereas only 2 of the 19 sets were submitted as highly meropenem-resistant strains (with an MIC of more than 1 mg/liter); thus, pbp1a-13 seems to affect penicillin more strongly than meropenem. In addition, given that the MIC of penicillin of the U.S. isolates with pbp1a-13 ranged from 1 to 8 mg/liter, the PBP profile, including all data for pbp1a, pbp2b, and pbp2x, could be helpful for the prediction of antimicrobial susceptibilities.

The analysis of conserved PBP amino acid motifs suggested that the amino acid substitutions of pbp1a SXXK, pbp2b SXN, and pbp2x SXXN intricately affected the susceptibility to penicillin, cefotaxime, and meropenem within serotype 19A-CC3111 isolates in Japan. Of note, we observed a wide distribution of all forms of antimicrobial susceptibility even when the isolates had the same conserved amino acid motifs. This finding could have been a consequence of the other conserved motif substitutions in any PBPs or of the non-PBP resistance mechanisms such as overexpression of murMN (22), mutation of GlcNAc deacetylase (23), etc.

In a phylogenetic analysis, we identified two resistant clusters in which the typical PBP profiles were pbp1a:pbp2b:pbp2x = JP2:16:112 (clusters 1, 2, and 3) and pbp1a:pbp2b:pbp2x = 13:24:112 (cluster 4). Although the MICs of penicillin, cefotaxime, and meropenem in the isolates of cluster 4 were higher than those in isolates of clusters 1 to 3, the conserved amino acid motifs analyzed in this study were completely identical in isolates with these two PBP profiles; it was difficult to predict drug susceptibilities only on the basis of the sequence of the conserved amino acid motifs. Therefore, in the whole-genome sequencing era, we should enhance the PBP profile database based on global isolates to report the correlation between profiles and antimicrobial susceptibilities to predict resistance. Although it is unclear whether the four resistant clones were from the same ancestor, there should be a certain genetic and/or environmental reason why the clones spread and became dominant in Japan. One of the possible explanations is that the spread was a consequence of pressure exerted by the PCVs. Interestingly, an estimation of when the most resistant clone (clone 4) branched from its ancestor showed that the date was 1965.4, although the 95% HPD of the divergence time had a very wide range. Considering that these resistant strains were rarely identified before the introduction of PCVs in Japan (24), that the serotype 19A-CC3111 clone is a Japanese-specific dominant clone, and that only two isolates from the United States and China were submitted to the MLST database, resistant serotype 19A-CC3111 may have arisen in Japan before the introduction of PCVs and then spread under the pressure of PCVs.

Most serotype 19A-CC3111 isolates in Japan harbored Tn2017, which contains mefE in MEGA and ermB in Tn917. Tn2017 was initially identified in a serotype 19F-ST1428 (CC271) isolate that was recovered in Hungary in 2003 (17); however, data regarding the prevalence of Tn2017 are limited. In Japan, the macrolide resistance rate is very high, at over 90% (8). In our previous study, we clarified that the dominant transposon that possessed ermB in serotype 15A-CC63 in Japan was Tn6002. Although the prevalence of this transposon type causing macrolide resistance in Japan is not well known, there was no correlation between the transposon types of the two predominant clones. The mechanism of increase in macrolide resistance in pneumococci has not been well studied, especially in its genomic aspects; therefore, further studies are needed.

There were some limitations of this study. First, the period for sample collection was relatively short (3 years), which may have influenced some results, especially in the estimation of divergence time in the BEAST analysis, as the 95% HPD of the divergence time had a broad range. To reveal the dynamics of the Japan-specific resistant clone in greater detail, additional studies with longer sampling times are needed. Second, we removed the recombination sites predicted by Gubbins in the BEAST analysis, a standard and commonly used approach for BEAST analysis. However, a limitation of this approach is that this method removes any substitutions that might have occurred after recombination events in the removed region. As a result, some substitutions that may influence genome evolution may not be evaluated in the Bayesian analysis.

In conclusion, we identified the prevalent pbp1a-13 allele in strains of serotype 19A-CC3111, which was the most prevalent clone in Japan after the introduction of PCVs. Phylogenetic analysis showed the existence of two resistant clones in serotype 19A-CC3111, whose PBP profiles were pbp1a:pbp2b:pbp2x = JP2:16:112 and pbp1a:pbp2b:pbp2x = 13:24:112. pbp1a-13 seemed to cause multidrug resistance in combination with an altered pbp2b and/or pbp2x type. For predicting the susceptibility of a pneumococcal isolate to penicillin, cephalosporin, and carbapenem, PBP profile analysis could be useful.

MATERIALS AND METHODS

Bacterial isolates.We conducted a nationwide, prospective surveillance study of pediatric IPDs and non-IPDs from January 2012 to December 2014 in Japan (7). Through the surveillance study, we collected 343 isolates from IPD cases and 286 isolates from non-IPD cases from a total of 154 medical institutions in Japan. Among these isolates, we obtained a total of 119 serotype 19A CC3111 isolates that were analyzed in this study. These isolates were obtained from 77 IPD patients and 42 non-IPD patients, including 36 otitis media and 6 pneumonia patients. The mean ages (ranges) of the IPD and the non-IPD patients were 20.4 (0 to 122) and 16.4 (0 to 43) months, respectively (see Table S1 in the supplemental material). Twenty-five IPD and 14 non-IPD patients were under 1 year of age.

Antimicrobial susceptibility definition.Based on the 2008 Clinical and Laboratory Standards Institute (CLSI) guidelines (25), we performed susceptibility testing for penicillin, cefotaxime, meropenem, and erythromycin using the broth microdilution method. Penicillin susceptibility (PCG-S) and resistance (PCG-R) MICs were defined as (in mg/liter) ≤0.06 and ≥0.12, respectively. Cefotaxime susceptibility (CTX-S), intermediate resistance (CTX-IR), and resistance (CTX-R) MICs were defined as (in mg/liter) ≤0.5, 1.0, and ≥2.0, respectively. Meropenem susceptibility (MEM-S), intermediate resistance (MEM-IR), and resistance (MEM-R) MICs were defined as (in mg/liter) ≤0.25, 0.5, and ≥1.0, respectively. Erythromycin susceptibility (EM-S) and resistance (EM-R) MICs were defined as (in mg/liter) ≤0.25 and ≥0.50, respectively.

Whole-genome sequencing.Of the 119 serotype 19A-CC3111 isolates described above, whole-genome sequencing data for seven isolates were obtained in the previous study (20). The sequencing data for the remaining 112 isolates were newly obtained in this study. The extraction of total genomic DNA and preparation of libraries for sequencing were performed following the methods described in the previous study (20). In this study, the samples were multiplexed and sequenced on an Illumina NextSeq sequencer for 300 cycles (2 × 150-bp paired-end sequencing). The isolates with an N50 value of <20,000 were excluded from subsequent analysis.

Penicillin-binding protein (PBP) typing, antimicrobial resistance genes, and pilus detection.We assigned PBP transpeptidase type numbers to the extracted PBP1a, PBP2b, and PBP2x transpeptidase sequences of the tested isolates according to the PBP types described by the CDC. In addition, we compared conserved amino acid motifs (SXXN, SSN, and KTG) of PBP1a, PBP2b, and PBP2x that were associated with penicillin, cefotaxime, and meropenem resistance (11). The type numbers originated from the CDC’s PBP type database (https://www.cdc.gov/streplab/pneumococcus/mic.html) (9, 12, 13, 21). PBP types that were not in the CDC database were given numbers with the prefix “JP” (e.g., “pbp1a-JP1”). In addition, we determined the presence of the ermB, ermTR, mefA, mefE, tetM, tetO, rrgA-1 (pili1), and pitB-1 (pili2) genes and searched for mutations within the folA and folP genes using assembled contigs with SPAdes v3.12.0 (9, 26). The details of the genomic analysis process are described in the supplemental material.

Phylogenetic analysis.We created a phylogenetic tree based on the core genome using RAxML v8.2.4 (27). The core genome of the 119 serotype 19A-CC3111 isolates was identified using Prokka v1.13 (28) and GET_HOMOLOGUES (29) with standard parameters. A maximum-likelihood phylogenetic tree was generated from the core genome alignment using RAxML with a GTRGAMMA DNA substitution model. Node support was assessed by using 500 bootstrap replicates.

Estimation of the date when the resistant serotype 19A-CC3111 clone originated.To estimate the date when the resistant serotype 19A-CC3111 strains branched from the common ancestor, we performed Bayesian analysis of the molecular sequences using BEAST v2.5.2 (30). We generated a reference file of the serotype 19A-CC3111 strains from the obtained contigs of the isolate with the highest N50 value by ordering and concatenating them using Mauve (31). The short reads of all tested isolates were mapped to the reference sequence using Burrows-Wheeler Aligner v0.7.17 (32), and recombination sites were identified using Gubbins v1.4.6 (33). A recombination-free alignment with 935,553 bp was used as input for BEAST analysis. For all serotype 19A-CC3111 isolates, a combination of strict and relaxed molecular clock models and constant, exponential, and Bayesian skyline models was tested using the recombination-free alignments. The best-fit model was chosen based on the results of path sampling. The Markov chain Monte Carlo length was set such that all output values had an effective sample size greater than 200.

Contents of Tn916-like integrative conjugative element.To clarify the structure of the Tn916-like integrative conjugative element (ICE), the corresponding regions were extracted from the assembled contigs. The reference sequence of Tn916 was submitted as NCBI reference sequence CR931676.1. The sequence was analyzed using ACT (34) with standard parameters in BLAST+ v2.6.0.

cps locus variation.To elucidate the genetic details of the serotype 19A cps locus, we obtained the sequence of the region by mapping short reads to the previously published reference sequence (35) (NCBI reference sequence: CR931676.1) using the Burrows-Wheeler Aligner v0.7.17 (32). After aligning the sequence, a phylogenetic tree was created using RAxML v8.2.4. with a GTRGAMMA DNA substitution model. Node support was assessed by using 500 bootstrap replicates.

Data availability.The reference sequence of Tn916 was submitted as NCBI reference sequence CR931676.1.

FOOTNOTES

    • Received 6 April 2019.
    • Returned for modification 8 May 2019.
    • Accepted 15 June 2019.
    • Accepted manuscript posted online 24 June 2019.

  • Supplemental material for this article may be found at https://doi.org/10.1128/AAC.00711-19.

REFERENCES

  1. 1.↵
    1. Wahl B,
    2. O'Brien KL,
    3. Greenbaum A,
    4. Majumder A,
    5. Liu L,
    6. Chu Y,
    7. Luksic I,
    8. Nair H,
    9. McAllister DA,
    10. Campbell H,
    11. Rudan I,
    12. Black R,
    13. Knoll MD
    . 2018. Burden of Streptococcus pneumoniae and Haemophilus influenzae type b disease in children in the era of conjugate vaccines: global, regional, and national estimates for 2000–15. Lancet Glob Health 6:e744–e757. doi:10.1016/S2214-109X(18)30247-X.
    OpenUrlCrossRef
  2. 2.↵
    1. Geno KA,
    2. Gilbert GL,
    3. Song JY,
    4. Skovsted IC,
    5. Klugman KP,
    6. Jones C,
    7. Konradsen HB,
    8. Nahm MH
    . 2015. Pneumococcal capsules and their types: past, present, and future. Clin Microbiol Rev 28:871–899. doi:10.1128/CMR.00024-15.
    OpenUrlAbstract/FREE Full Text
  3. 3.↵
    1. Chiba N,
    2. Morozumi M,
    3. Shouji M,
    4. Wajima T,
    5. Iwata S,
    6. Sunakawa K,
    7. Ubukata K
    . 2013. Rapid decrease of 7-valent conjugate vaccine coverage for invasive pneumococcal diseases in pediatric patients in Japan. Microb Drug Resist 19:308–315. doi:10.1089/mdr.2012.0180.
    OpenUrlCrossRefPubMed
  4. 4.↵
    1. Waight PA,
    2. Andrews NJ,
    3. Ladhani NJ,
    4. Sheppard CL,
    5. Slack MP,
    6. Miller E
    . 2015. Effect of the 13-valent pneumococcal conjugate vaccine on invasive pneumococcal disease in England and Wales 4 years after its introduction: an observational cohort study. Lancet Infect Dis 15:629. doi:10.1016/S1473-3099(15)00028-6.
    OpenUrlCrossRef
  5. 5.↵
    1. Abat C,
    2. Raoult D,
    3. Rolain JM
    . 2015. Dramatic decrease of Streptococcus pneumoniae infections in Marseille, 2003–2014. Eur J Clin Microbiol Infect Dis 34:2081–2087. doi:10.1007/s10096-015-2455-1.
    OpenUrlCrossRef
  6. 6.↵
    1. Camilli R,
    2. D'Ambrosio F,
    3. Del Grosso M,
    4. Pimentel de Araujo F,
    5. Caporali MG,
    6. Del Manso M,
    7. Gherardi G,
    8. D'Ancona F,
    9. Pantosti A
    . 2017. Impact of pneumococcal conjugate vaccine (PCV7 and PCV13) on pneumococcal invasive diseases in Italian children and insight into evolution of pneumococcal population structure. Vaccine 35:4587–4593. doi:10.1016/j.vaccine.2017.07.010.
    OpenUrlCrossRef
  7. 7.↵
    1. Moore MR,
    2. Link-Gelles R,
    3. Schaffner W,
    4. Lynfield R,
    5. Holtzman C,
    6. Harrison LH,
    7. Zansky SM,
    8. Rosen JB,
    9. Reingold A,
    10. Scherzinger K,
    11. Thomas A,
    12. Guevara RE,
    13. Motala T,
    14. Eason J,
    15. Barnes M,
    16. Petit S,
    17. Farley MM,
    18. McGee L,
    19. Jorgensen JH,
    20. Whitney CG
    . 2016. Effectiveness of 13-valent pneumococcal conjugate vaccine for prevention of invasive pneumococcal disease in children in the USA: a matched case-control study. Lancet Respir Med 4:399–406. doi:10.1016/S2213-2600(16)00052-7.
    OpenUrlCrossRef
  8. 8.↵
    1. Nakano S,
    2. Fujisawa T,
    3. Ito Y,
    4. Chang B,
    5. Suga S,
    6. Noguchi T,
    7. Yamamoto M,
    8. Matsumura Y,
    9. Nagao M,
    10. Takakura S,
    11. Ohnishi M,
    12. Ihara T,
    13. Ichiyama S
    . 2016. Serotypes, antimicrobial susceptibility, and molecular epidemiology of invasive and non-invasive Streptococcus pneumoniae isolates in paediatric patients after the introduction of 13-valent conjugate vaccine in a nationwide surveillance study conducted in Japan in 2012-2014. Vaccine 34:67–76. doi:10.1016/j.vaccine.2015.11.015.
    OpenUrlCrossRef
  9. 9.↵
    1. Metcalf BJ,
    2. Gertz RE, Jr,
    3. Gladstone RA,
    4. Walker H,
    5. Sherwood LK,
    6. Jackson D,
    7. Li Z,
    8. Law C,
    9. Hawkins PA,
    10. Chochua S,
    11. Sheth M,
    12. Rayamajhi N,
    13. Bentley SD,
    14. Kim L,
    15. Whitney CG,
    16. McGee L,
    17. Beall B
    . 2016. Strain features and distributions in pneumococci from children with invasive disease before and after 13-valent conjugate vaccine implementation in the USA. Clin Microbiol Infect 22:60.e9–60.e29. doi:10.1016/j.cmi.2015.08.027.
    OpenUrlCrossRef
  10. 10.↵
    1. Adam HJ,
    2. Golden AR,
    3. Karlowsky JA,
    4. Baxter MR,
    5. Nichol KA,
    6. Martin I,
    7. Demczuk W,
    8. Mulvey MR,
    9. Gilmour MW,
    10. Hoban DJ,
    11. Zhanel GG
    . 2018. Analysis of multidrug resistance in the predominant Streptococcus pneumoniae serotypes in Canada: the SAVE study, 2011–15. J Antimicrob Chemother 73:vii12–vii19. doi:10.1093/jac/dky158.
    OpenUrlCrossRef
  11. 11.↵
    1. Hakenbeck R,
    2. Bruckner R,
    3. Denapaite D,
    4. Maurer P
    . 2012. Molecular mechanisms of beta-lactam resistance in Streptococcus pneumoniae. Future Microbiol 7:395–410. doi:10.2217/fmb.12.2.
    OpenUrlCrossRefPubMedWeb of Science
  12. 12.↵
    1. Metcalf BJ,
    2. Chochua S,
    3. Gertz RE,
    4. Li Z,
    5. Walker H,
    6. Tran T,
    7. Hawkins PA,
    8. Glennen A,
    9. Lynfield R,
    10. Li Y,
    11. McGee L,
    12. Beall B
    ; Active Bacterial Core surveillance team. 2016. Using whole genome sequencing to identify resistance determinants and predict antimicrobial resistance phenotypes for year 2015 invasive pneumococcal disease isolates recovered in the United States. Clin Microbiol Infect 22:1002.e1–1002.e8. doi:10.1016/j.cmi.2016.08.001.
    OpenUrlCrossRef
  13. 13.↵
    1. Li Y,
    2. Metcalf BJ,
    3. Chochua S,
    4. Li Z,
    5. Gertz RE, Jr,
    6. Walker H,
    7. Hawkins PA,
    8. Tran T,
    9. Whitney CG,
    10. McGee L,
    11. Beall BW
    . 2016. Penicillin-binding protein transpeptidase signatures for tracking and predicting beta-lactam resistance levels in Streptococcus pneumoniae. mBio 7:e00756-16. doi:10.1128/mBio.00756-16.
    OpenUrlAbstract/FREE Full Text
  14. 14.↵
    1. van der Linden M,
    2. Perniciaro S,
    3. Imöhl M
    . 2015. Increase of serotypes 15A and 23B in IPD in Germany in the PCV13 vaccination era. BMC Infect Dis 15:207. doi:10.1186/s12879-015-0941-9.
    OpenUrlCrossRef
  15. 15.↵
    1. Del Grosso M,
    2. Scotto d'Abusco A,
    3. Iannelli F,
    4. Pozzi G,
    5. Pantosti A
    . 2004. Tn2009, a Tn916-like element containing mef(E) in Streptococcus pneumoniae. Antimicrob Agents Chemother 48:2037–2042. doi:10.1128/AAC.48.6.2037-2042.2004.
    OpenUrlAbstract/FREE Full Text
  16. 16.↵
    1. Marimón JM,
    2. Valiente A,
    3. Ercibengoa M,
    4. García-Arenzana JM,
    5. Pérez-Trallero E
    . 2005. Erythromycin resistance and genetic elements carrying macrolide efflux genes in Streptococcus agalactiae. Antimicrob Agents Chemother 49:5069–5074. doi:10.1128/AAC.49.12.5069-5074.2005.
    OpenUrlAbstract/FREE Full Text
  17. 17.↵
    1. Del Grosso M,
    2. Camilli R,
    3. Libisch B,
    4. Fuzi M,
    5. Pantosti A
    . 2009. New composite genetic element of the Tn916 family with dual macrolide resistance genes in a Streptococcus pneumoniae isolate belonging to clonal complex 271. Antimicrob Agents Chemother 53:1293–1294. doi:10.1128/AAC.01066-08.
    OpenUrlFREE Full Text
  18. 18.↵
    1. Warburton PJ,
    2. Palmer RM,
    3. Munson MA,
    4. Wade WG
    . 2007. Demonstration of in vivo transfer of doxycycline resistance mediated by a novel transposon. J Antimicrob Chemother 60:973–980. doi:10.1093/jac/dkm331.
    OpenUrlCrossRefPubMedWeb of Science
  19. 19.↵
    1. Nakano S,
    2. Fujisawa T,
    3. Ito Y,
    4. Chang B,
    5. Matsumura Y,
    6. Yamamoto M,
    7. Suga S,
    8. Ohnishi M,
    9. Nagao M
    . 25 April 2019, posting date. Whole-genome sequencing analysis of multidrug-resistant serotype 15a Streptococcus pneumoniae in Japan and the emergence of a highly resistant serotype 15A-ST9084 clone. Antimicrob Agents Chemother doi:10.1128/AAC.02579-18.
    OpenUrlAbstract/FREE Full Text
  20. 20.↵
    1. Nakano S,
    2. Fujisawa T,
    3. Ito Y,
    4. Chang B,
    5. Matsumura Y,
    6. Yamamoto M,
    7. Nagao M,
    8. Suga S,
    9. Ohnishi M,
    10. Ichiyama S
    . 2018. Spread of meropenem-resistant Streptococcus pneumoniae serotype 15A-ST63 clone in Japan, 2012–2014. Emerg Infect Dis 24:275–283. doi:10.3201/eid2402.171268.
    OpenUrlCrossRef
  21. 21.↵
    Centers for Disease Control and Prevention. 2019. Minimum inhibitory concentrations predicted by the penicillin binding protein type. https://www.cdc.gov/streplab/mic-tables.html. Accessed 10 July 2019.
  22. 22.↵
    1. Filipe SR,
    2. Severina E,
    3. Tomasz A
    . 2002. The murMN operon: a functional link between antibiotic resistance and antibiotic tolerance in Streptococcus pneumoniae. Proc Natl Acad Sci U S A 99:1550–1555. doi:10.1073/pnas.032671699.
    OpenUrlAbstract/FREE Full Text
  23. 23.↵
    1. Tait-Kamradt AG,
    2. Cronan M,
    3. Dougherty TJ
    . 2009. Comparative genome analysis of high-level penicillin resistance in Streptococcus pneumoniae. Microb Drug Resist 15:69–75. doi:10.1089/mdr.2009.0891.
    OpenUrlCrossRefPubMedWeb of Science
  24. 24.↵
    1. Sakai F,
    2. Chiba N,
    3. Ono A,
    4. Yamagata Murayama S,
    5. Ubukata K,
    6. Sunakawa K,
    7. Takahashi T
    . 2011. Molecular epidemiologic characteristics of Streptococcus pneumoniae isolates from children with meningitis in Japan from 2007 through 2009. J Infect Chemother 17:334–340. doi:10.1007/s10156-010-0180-3.
    OpenUrlCrossRefPubMed
  25. 25.↵
    CLSI. 2015. Performance standards for antimicrobial susceptibility testing; twenty-fifth informational supplement. CLSI document M100-S25. Clinical and Laboratory Standards Institute, Wayne, PA.
  26. 26.↵
    1. Bankevich A,
    2. Nurk S,
    3. Antipov D,
    4. Gurevich AA,
    5. Dvorkin M,
    6. Kulikov AS,
    7. Lesin VM,
    8. Nikolenko SI,
    9. Pham S,
    10. Prjibelski AD,
    11. Pyshkin AV,
    12. Sirotkin AV,
    13. Vyahhi N,
    14. Tesler G,
    15. Alekseyev MA,
    16. Pevzner PA
    . 2012. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 19:455–477. doi:10.1089/cmb.2012.0021.
    OpenUrlCrossRefPubMed
  27. 27.↵
    1. Stamatakis A
    . 2014. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30:1312–1313. doi:10.1093/bioinformatics/btu033.
    OpenUrlCrossRefPubMedWeb of Science
  28. 28.↵
    1. Seemann T
    . 2014. Prokka: rapid prokaryotic genome annotation. Bioinformatics 30:2068–2069. doi:10.1093/bioinformatics/btu153.
    OpenUrlCrossRefPubMedWeb of Science
  29. 29.↵
    1. Contreras-Moreira B,
    2. Vinuesa P
    . 2013. GET_HOMOLOGUES, a versatile software package for scalable and robust microbial pangenome analysis. Appl Environ Microbiol 79:7696–7701. doi:10.1128/AEM.02411-13.
    OpenUrlAbstract/FREE Full Text
  30. 30.↵
    1. Drummond AJ,
    2. Rambaut A
    . 2007. BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol Biol 7:214. doi:10.1186/1471-2148-7-214.
    OpenUrlCrossRefPubMed
  31. 31.↵
    1. Darling AC,
    2. Mau B,
    3. Blattner FR,
    4. Perna NT
    . 2004. Mauve: multiple alignment of conserved genomic sequence with rearrangements. Genome Res 14:1394–1403. doi:10.1101/gr.2289704.
    OpenUrlAbstract/FREE Full Text
  32. 32.↵
    1. Li H,
    2. Durbin R
    . 2009. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25:1754–1760. doi:10.1093/bioinformatics/btp324.
    OpenUrlCrossRefPubMedWeb of Science
  33. 33.↵
    1. Croucher NJ,
    2. Page AJ,
    3. Connor TR,
    4. Delaney AJ,
    5. Keane JA,
    6. Bentley SD,
    7. Parkhill J,
    8. Harris SR
    . 2015. Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins. Nucleic Acids Res 43:e15. doi:10.1093/nar/gku1196.
    OpenUrlCrossRefPubMed
  34. 34.↵
    1. Carver T,
    2. Berriman M,
    3. Tivey A,
    4. Patel C,
    5. Bohme U,
    6. Barrell BG,
    7. Parkhill J,
    8. Rajandream MA
    . 2008. Artemis and ACT: viewing, annotating and comparing sequences stored in a relational database. Bioinformatics 24:2672–2676. doi:10.1093/bioinformatics/btn529.
    OpenUrlCrossRefPubMedWeb of Science
  35. 35.↵
    1. Bentley SD,
    2. Aanensen DM,
    3. Mavroidi A,
    4. Saunders D,
    5. Rabbinowitsch E,
    6. Collins M,
    7. Donohoe K,
    8. Harris D,
    9. Murphy L,
    10. Quail MA,
    11. Samuel G,
    12. Skovsted IC,
    13. Kaltoft MS,
    14. Barrell B,
    15. Reeves PR,
    16. Parkhill J,
    17. Spratt BG
    . 2006. Genetic analysis of the capsular biosynthetic locus from all 90 pneumococcal serotypes. PLoS Genet 2:e31. doi:10.1371/journal.pgen.0020031.
    OpenUrlCrossRefPubMed
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KEYWORDS

19A
Japan
PBP typing
ST3111
Streptococcus pneumoniae
meropenem
multidrug resistance
PBP1a
pbp2b
PBP2x

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