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1 Department of Bacteriology, Food Research Institute, University of Wisconsin-Madison, Madison, WI 53706, USA
2 National Food Safety & Toxicology Center, Michigan State University, East Lansing, MI 48824-1314, USA
Correspondence
Eric A. Johnson
eajohnso{at}wisc.edu
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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The GenBank accession numbers for genes bont/a1, bont/a2, bont/a3, bont/a4, bont/b and the silent bont/b are AF461539, AY953275, DQ185900, DQ185901, EU341304 and NCTC 2916, respectively. Accession numbers for sequences of the genes rpoB, recA, oppB, mdh, hsp60, aceK and aroE are EU372261–EU372269, EU372253–EU372260, EU372242–EU372252, EU372232–EU372241, EU372223–EU372231, EU372210–EU372222 and EU372197–EU372209, respectively.
A supplementary table of primers and a supplementary figure showing the genomic locations of the loci analysed are available with the online version of this paper.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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). BoNTs have traditionally been immunologically distinguished into seven serotypes (BoNT/A–G), among which BoNTs A, B, E and F are known to cause human botulism (Hatheway & Johnson, 1998; Smith & Sugiyama, 1988; Smith & Moryson, 1977). Type A is a representative of C. botulinum group I proteolytic strains as it demonstrates close similarity to proteolytic type F and B strains (Collins & Lawson, 1994). This is of particular importance and interest since it causes the most severe human botulism (Woodruff et al., 1992), is considered to be the most significant bioterrorism threat and has been increasingly used as a pharmaceutical modality (Johnson et al., 2005).
Recent findings have shown that BoNT/A has substantial sequence diversity and four subtypes have so far been identified (Arndt et al., 2006; Kozaki et al., 1995; Smith et al., 2005). Such sequence variation is not limited to type A, as more than 46 subtypes exist for serotypes A–G (Gimenez & Gimenez, 1995; Smith et al., 2005). With regard to the bont/a gene, it has been represented by bont/a1 (NCBI accession number AF461539), bont/a2 (AY953275), bont/a3 (DQ185900) and bont/a4 (DQ185901).
Previous studies have also identified extensive genotypic and phenotypic diversity in these strains (Hatheway & Johnson, 1998; Johnson & Bradshaw, 2001; Kozaki et al., 1995; Smith et al., 2005). To date, phylogenetic analysis and typing of C. botulinum by genetic methods has mainly focused on PFGE, ribotyping (rRNA analysis), amplified fragment length polymorphism (AFLP), randomly amplified polymorphic DNA analysis (RAPD) and repetitive element sequence-based PCR (Rep-PCR) (Lindstrom & Korkeala, 2006). Although these techniques have utility, they also have disadvantages. For instance, rRNA analysis focuses on a single locus only and may not represent the diversity of the genome in the species; and PFGE is based on determination of restriction digest polymorphisms which is labour intensive, may vary between different laboratories and is difficult to use for identifying phylogenetic lineages (Hill et al., 2007; Johnson et al., 2005; Noller et al., 2003).
Therefore, a sequence-based system for assessing genetic relatedness among isolates would be useful in study of this pathogen. Multi-locus sequence typing (MLST) is a method currently being implemented in many laboratories as a means of determining the degree of evolutionary relatedness among various strains of bacterial and eukaryotic species (Gatei et al., 2007; Jost et al., 2006; Lacher et al., 2007; Maiden, 2006; Vassileva et al., 2006; Zadoks et al., 2005). MLST was initially demonstrated in 1998 to be effective in studying the phylogeny of bacteria (Maiden et al., 1998). Since this pioneering study, MLST has been shown to be a useful method for bacterial typing as it has broad applicability in both the range of organisms that can be studied and the breadth of practical and conceptual problems that can be addressed (Urwin & Maiden, 2003). MLST combines advances in high-throughput sequencing, population genetics and bioinformatics to provide a tool for the study of population and evolutionary biology of various organisms. In this study, we applied MLST analysis for assessing the genetic relatedness of C. botulinum type A strains.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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) are from E. A. J.'s laboratory strain collection. Cultures were grown in 10 ml TPGY medium (per litre: 50 g trypticase peptone, 5 g Bacto peptone, 4 g D-glucose, 20 g yeast extract, 1 g cysteine.HCl, pH 7.4) for 2 days at 37 °C.
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). DNA was then diluted to 50 ng µl–1 and used for PCR amplification.
PCR amplification and sequencing.
PCR amplifications were performed using the GeneAmp High Fidelity PCR System (Applied BioSystems). PCR cycles were as follows: 95 °C for 2 min, followed by 25 cycles of 95 °C for 1 min, an annealing step for 45 s, 72 °C for extension, followed by 1 cycle of 72 °C extension for 10 min. Annealing temperatures of the different primers are given in Table 2 and Supplementary Table S1, available with the online version of this paper. Extension time was dependent on the length of the amplification product (see Table S1); in general, a 1 min extension step was utilized to extend a 1 kb fragment. Following amplification, all PCR products were isolated using the PureLink PCR Purification kit (Invitrogen). Sequencing preparations were produced using conditions advised by the University of Wisconsin Biotechnology Center for the ABI PRISM BigDye Cycle Sequencing kit (Applied BioSystems). Sequencing analysis was performed at the University of Wisconsin Biotechnology Center and final sequencing results were analysed using the Vector NTI Suite Program (Invitrogen). Accession numbers for the resulting nucleotide sequences are as follows: rpoB, EU372261–EU372269; recA, EU372253–EU372260; oppB, EU372242–EU372252; mdh, EU372232–EU372241; hsp60, EU372223–EU372231; aceK, EU372210–EU372222; and aroE, EU372197–EU372209.
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) was used to identify various loci for MLST analysis. Genes were chosen for MLST analyses mainly based on their utility in the studies of other bacterial species. Once the 14 genes were selected, the entire ORF of each was used to select primers for initial analysis.
In the initial analysis by MLST to assess its applicability to the C. botulinum group, 30 isolates (Table 1
) were analysed by performing PCR on 14 genes (Table S1) which were sequenced using an overlapping gene sequencing approach. The primers used to amplify the complete coding frame and the internal primers used in subsequent sequencing reactions are listed in Table 2. After this analysis was complete, specific regions of all 14 genes were analysed for the 30 strains to determine which regions contained the optimum degree of divergence to allow for proper MLST analysis. While all 14 genes showed divergence, seven genes were chosen to facilitate further MLST analysis and enable the creation of subfamilies. Regions were evaluated and then entered into the Primer3 program (Rozen & Skaletsky, 2000) to amplify a 700–800 bp section (see Table 2 for primer sequence and gene-specific location). These primers were then used in the PCR amplification of designated gene products.
When final MLST primers had been designed, PCR reactions were performed on 73 isolates (Table 1). Most of these isolates were known type A strains from the A1, A2, A3, A4 and A(B) groups. C. botulinum type A neurotoxin was not used as a gene for MLST analysis in order to make the procedure as broad as possible and allow for potential analysis of Clostridium strains with other BoNT serotypes using the procedure.
Analysis of MLST data.
Sequences were assembled from the resultant chromatograms using the ContigExpress program within Vector NTI (Invitrogen). For each of the seven loci, each sequence obtained was assigned a distinct allele number. Each isolate is defined by an allelic profile consisting of seven integers, which corresponds to the allele numbers at the seven loci of recA, rpoB, oppB, hsp60, aceK, mdh and aroE. The unique allelic profiles were assigned a sequence type (ST). The resulting STs were analysed using the program's sequence type analysis and recombination tests (START) (Jolley et al., 2001) to organize the various data. Further analysis was conducted using MEGA3 (Kumar et al., 2004) to identify relationships among the various strains. The final data were compiled and submitted for hosting at http://pubmlst.org/cbotulinum/ (Jolley et al., 2004).
Neighbour-joining (NJ) trees were constructed using the Kimura two-parameter model of nucleotide substitution with the MEGA3 software and the inferred phylogenies were each tested with 500 bootstrap replications. Phylogenetic network analysis was conducted with the SplitsTree 4 program (Huson & Bryant, 2006) using the neighbour-net algorithm (Bryant & Moulton, 2004) and untransformed distances (p distance). The number of synonymous substitutions per synonymous site (dS) and the number of nonsynonymous substitutions per nonsynonymous site (dN) were estimated by the modified Nei–Gojobori method using MEGA3 (Kumar et al., 2004). Allelic sequences were fitted to a nucleotide substitution model using the Datamonkey website. Single likelihood ancestor counting (SLAC) was used to fit a codon model to detect selection on individual codons (Pond & Frost, 2005). The SLAC method was also used to calculate the ratio of dN to dS and estimate the 95 % confidence interval. The 
w recombination test (Bruen et al., 2006), as implemented by SplitsTree 4, was used to distinguish recurrent mutation from recombination in generating genotypic diversity.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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and Supplementary Table S1). After analysing the sequence data, seven housekeeping genes (rpoB, mdh, aroE, hsp60, aceK, oppB and recA) were selected because of their inherent genetic variability and placement in the C. botulinum genome, so that the MLST scheme would have an approximately even distribution throughout the genome (Supplementary Fig. S1). Following this strategy, the seven housekeeping genes of 73 strains of C. botulinum and related clostridia were sequenced with appropriate primers (Tables 1 and 2).
Creation of MLST ST profiles
MLST analysis of 73 C. botulinum and related clostridia yielded locus frequencies that ranged from 8 to 13 alleles per locus (Table 1); 24 unique profile patterns or STs were identified. ST-1 encompassed 29 strains including subtype A1 and A(B) strains; ST-4 included 13 A(B) strains; ST-5 included 3 A(B) strains and ST-9 included 3 A1 strains. STs 2, 6, 7, 8 and 11 were represented by 2 strains, each covering a wide array of subtypes including A2, A(B), A4 and A1 (Table 1).
Evaluation of MLST ST profiles
To compare the level of sequence divergence as measured by MLST, we constructed a NJ dendrogram showing the genetic relatedness among the 24 STs (Fig. 1a). Bootstrap analysis classified the STs into four main groups with genetic distance greater than 0.01. The most divergent strains were in ST-5 and ST-17, which was surprising since ST-5 comprised a set of A(B) strains and ST-17 was a BoNT/A1-producing strain. These strains were expected to be more closely related to those possessing the same subtype of BoNT. Their relatively large differentiation from the other strains may indicate that they had split from the main family of C. botulinum early in the overall evolution of the species. The fact that they have the same neurotoxin sequence as the other strains supports the view that the evolution of BoNT is not linked to the evolution of the species in toto. Four STs (3, 7, 14 and 18) formed a separate group; ST-7, ST-14 and ST-18 were closely related, which was supported by 100 % bootstrap analysis. This cluster of STs is interesting since they are all composed of strains with different BoNT sequences; these are BoNT/A(B), BoNT/A4 and BoNT/A1 with an A2 cluster, respectively. The 18 remaining strains formed a closely related group with two subgroups; the largest group of nine STs (6, 12, 4, 2, 22, 23, 15, 8 and 10) had diverse BoNT profiles, while the A2 and A(B) groups had 90 % bootstrap support and seven STs (19, 9, 11, 1, 24, 20 and 21), largely composed of BoNT/A1-producing strains, had 88 % bootstrap support (Fig. 1a).
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) based on SplitsTree analysis (Bryant & Moulton, 2004). This analysis does not force the sequence data into a bifurcating tree and allows for numerous parallel paths indicative of the presence of phylogenetic incompatibilities in the divergence of STs. Such incompatibilities could arise from recombination or recurrent mutations in the MLST loci. To detect recombination, we used the w test, which has been shown in SplitsTree analysis to discriminate between recurrent mutations and recombination in a variety of circumstances (Bruen et al., 2006). In relation to the concatenated sequences of the 241 STs, there were 151 informative sites and the w test was found to show statistically significant evidence of recombination (P<0.001). Interestingly, although there is significant recombination among very clearly related STs, there is no evidence of recombination among the more distantly related strains matched by STs 3, 5, 7, 14, 17 and 18 (Fig. 1b). This result is intriguing considering the observation that there is a low degree of similarity between the strains in these STs at the BoNT level. In fact, all but two of these STs have their own unique BoNT profile, as only ST-5 and ST-14 have A(B) profiles. The remainder of the STs all represent unique strains with different neurotoxin profiles ranging from strains with a BoNT/A1 gene to more distinct strains, such as those that have a BoNT/A3, BoNT/A4 or a BoNT/A1 gene with an A2 cluster. |
DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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). The genes chosen for MLST analysis in this study were selected because of their utility in previous MLST studies with other bacterial species and their distinct distribution in the C. botulinum chromosome. Initial analysis of 14 candidate genes was combined with the genomic location of each gene estimated from the genome sequence of C. botulinum ATCC 3502 to determine seven genes that provided a representation of the genetic relatedness of the strains on a genome scale. The loci used in the final analysis were hsp60, rpoB, oppB, mdh, recA, aceK and aroE. Based on MLST studies of other pathogenic bacterial species, it is common to include a virulence gene as one of the loci used to determine genetic relationships within a bacterial group. In our analysis, this strategy was not followed since the BoNT gene does not have sufficiently distinct loci that could be used for MLST analysis. Further, it would limit the applicability of the MLST system to other C. botulinum serotypes and neurotoxigenic clostridia of different species. At this time, five alleles of this gene have been described [A1, A2, A3, A4 and A1 in A(B) strains], which would not provide adequate genetic variation for MLST analysis.
There are several other genes associated with BoNT that could be used to study genetic variation, but were again not chosen for analysis; these include genes within the distinct toxin gene clusters in type A (Jacobson et al., 2008). There are two primary types of neurotoxin clusters in C. botulinum type A (Jacobson et al., 2008). The difference between the two basic clusters is substantial, as three of the four genes consist of either a set of haemagglutinin (HA) genes or a set of genes of unknown function called ‘orfx’s. The only gene that is common among the clusters is the nontoxic nonhaemagglutinin gene, ntnh. However, ntnh would pose problems if used as an MLST locus since two copies are present in strains with bivalent designations, such as A(B). Therefore, we selected seven housekeeping genes spread evenly across the genome for the MLST analysis and did not include the BoNT gene or genes within the BoNT clusters.
Several interesting results emerged from this study, specifically that there appears to be a significant amount of genetic association between the A1 and A(B) strains, since there was intersection between the two types in several ST groups, particularly ST-1 (Table 1). There are several possible hypotheses to explain this diversity. The most likely is that the evolution of the BoNT/A genes and their respective gene clusters differs significantly from the evolution of the species in toto. This hypothesis is supported by other observations related to evolution of BoNT/A and toxin gene clusters. Since BoNT acts solely on the nervous systems of higher eukaryotes, the selective pressure for its evolution is enigmatic. The BoNT gene and the structure of BoNT/A and BoNT/B have a highly mosaic composition (Arndt et al., 2006). The composition of the toxin gene clusters may have resulted from acquisition of eukaryotic genes, e.g. by viral infection, and from gene transfer that occurred during evolution of C. botulinum (DasGupta, 2006; Johnson & Bradshaw, 2001). This would explain how members of this species, which differ widely in genetic and phenotypic properties, possess BoNT/A genes and an associated protein cluster that are highly conserved. It would also explain why certain C. botulinum isolates such as those possessing the BoNT/A3 and BoNT/A4 genes have such a low degree of relatedness compared to strains possessing BoNT/A1 gene, while the BoNT/A genes have relatively high homology of 80–90 %.
The MLST analysis also supports the theory that recombination was a prominent driving force contributing to the relatedness of the strains tested in this study. However, there were a few outliers (STs 3, 5, 7, 14, 17 and 18). The uniqueness of the BoNT sequences of most of these strains suggests that they may have been geographically or ecologically isolated, meaning that there was limited interaction with other strains within the C. botulinum species. This could in turn explain why the BoNT profiles of these strains are unique, as it is possible that they may have evolved to different degrees with respect to eukaryotic gene acquisition, gene transfer and recombination. This hypothesis is supported by the unique ST-3 pattern of BoNT/A3 strains, as only one outbreak of botulism has been attributed to BoNT/A3, whereas BoNT/A1 and BoNT/A2 have been involved in numerous botulism outbreaks.
Another set of interesting outliers in this study were ST-5 and ST-17. At this time, there is little known about the strains possessing these STs. The three strains in ST-5 are A(B) strains, while the one ST-17 is an A1 strain: each is distinct from other analysed strains. Initial experiments performed in our laboratory have indicated that the ST-5 bacteria possess a unique neurotoxin cluster arrangement compared to the standard clusters observed in the literature (Jacobson et al., 2008).
Additionally, strain 5328A (ST-18) has a BoNT/A1 gene associated with an orfx cluster arrangement that is similar to that seen in C. botulinum strains that have the BoNT/A2 gene. This type of cluster arrangement is present in about half of BoNT/A1 strains, but only when a BoNT/B silent gene is also present and associated with a HA cluster. Strain 5328A lacks the BoNT/B silent gene cluster and has only a BoNT/A1 cluster. This appears to be unusual but becomes more revealing when compared with an A(B) strain and the BoNT/A4 strain, which also has a BoNT/B gene cluster. The implications of both the lack of a cryptic BoNT/B and its relatedness to these other strains have yet to be completely explained and will require further analysis.
In summary, MLST is a nucleotide sequence-based approach with many advantages for subtyping and phylogenetic analysis of various organisms. We show in this study that MLST is an efficient and discriminatory method for strain differentiation and phylogenetic analysis of C. botulinum. Twenty-four unique ST lineages were identified from analysis of 73 C. botulinum type A strains. In future studies, we will expand this MLST procedure to other BoNT-producing bacteria including serotypes B–G. This will be of value in further elucidating and understanding the genetic relatedness in this diverse species. Lastly, this strategy may also be applicable to phylogenetic studies of other Clostridium species.
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ACKNOWLEDGEMENTS |
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Edited by: S. D. Bentley
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Received 17 January 2008;
revised 13 April 2008;
accepted 14 April 2008.
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