Recombinational Switching of the Clostridium difficile S-Layer and a Novel Glycosylation Gene Cluster Revealed by Large-Scale Whole-Genome Sequencing

Abstract

Background. Clostridium difficile is a major cause of nosocomial diarrhea, with 30-day mortality reaching 30%. The cell surface comprises a paracrystalline proteinaceous S-layer encoded by the slpA gene within the cell wall protein (cwp) gene cluster. Our purpose was to understand the diversity and evolution of slpA and nearby genes also encoding immunodominant cell surface antigens.

Methods. Whole-genome sequences were determined for 57 C. difficile isolates representative of the population structure and different clinical phenotypes. Phylogenetic analyses were performed on their genomic region (>63 kb) spanning the cwp cluster.

Results. Genetic diversity across the cwp cluster peaked within slpA, cwp66 (adhesin), and secA2 (secretory translocase). These genes formed a 10-kb cassette, of which 12 divergent variants were found. Homologous recombination involving this cassette caused it to associate randomly with genotype. One cassette contained a novel insertion (length, approximately 24 kb) that resembled S-layer glycosylation gene clusters.

Conclusions. Genetic exchange of S-layer cassettes parallels polysaccharide capsular switching in other species. Both cause major antigenic shifts, while the remainder of the genome is unchanged. C. difficile genotype is therefore not predictive of antigenic type. S-layer switching and immune escape could help explain temporal and geographic variation in C. difficile epidemiology and may inform genotyping and vaccination strategies.

The severity of an infectious disease is determined by 2 key opposing factors: the virulence of the invading pathogen and the success of the host defense. Both factors are influenced by the outer surface of the bacterial cell, which is under strong immune selection for high antigenic diversity and rapid evolutionary change. As this process can quickly transform the epidemiology of an infection [1, 2], it is important to understand bacterial antigenic repertoires and the mechanisms by which they evolve.

The high diversity of genes encoding cell surface antigens can preclude their large-scale characterization by conventional Sanger DNA sequencing, since to be performed at high throughput this technique requires prior knowledge of gene content and nucleotide sequence. Recent advances in DNA sequencing technology [3] offer many new opportunities to clinical microbiology [4], including the chance to understand the diversity and evolution of previously intransigent species. An example is Clostridium difficile, a Gram-positive sporulating anaerobe that has become an important nosocomial and community-acquired human pathogen [5]. The loci encoding 2 of its major cell surface antigens exhibit high genetic diversity between strains [6, 7], but they have only been investigated on a small scale [7, 8].

C. difficile infections (CDIs) range in severity from mild diarrhea to pseudomembranous colitis and toxic megacolon, with a crude 30-day mortality that can exceed 30% [9]. C. difficile virulence is multifactorial and includes variable toxigenicity and transmissibility [10]. Two hypervirulent strains (polymerase chain reaction [PCR] ribotypes 027 and 078) associated with poor clinical outcome have been identified in recent years [11, 12]. However, the contribution of the outer cell surface to C. difficile virulence is poorly understood.

C. difficile is one of many bacterial species surrounded by a paracrystalline S-layer, which self-assembles from multiple copies of a single protein [13]. The C. difficile S-layer is encoded by the slpA gene, located within a 36.6-kb cell wall protein (cwp) gene cluster [14]. Bacterial S-layers are in many cases glycosylated, a post-translational modification that is encoded by a characteristic gene cluster located near the S-layer gene [15]. However, neither genetic nor phenotypic evidence of S-layer glycosylation has been found in C. difficile to date [14, 16].

The C. difficile S-layer protein is an immunodominant antigen, activating both innate and adaptive immunity, and providing the basis for C. difficile serological typing [17–19]. The S-layer precursor protein is cleaved after translation into high-molecular-weight and low-molecular-weight (LMW) fragments [8]. The LMW fragment exhibits extremely high genetic diversity between serogroups, which consequently lack immunological cross-reactivity [6, 8, 13]. Within a serogroup, the slpA nucleotide sequences show little variability [19]. These observations are consistent with mathematical models predicting that intense immune selection will polarize strains into distinct, non–cross-reactive antigenic types [20]. A second major C. difficile cell surface antigen is Cwp66, an adhesin that is also a member of the cwp cluster, exhibits high genetic diversity, and elicits a strong immune response [7, 21]. Both Cwp66 and S-layer proteins are exported from the cell by a secretory system, the specificity of which is redirected by the protein SecA2 [22]. SecA2 is encoded within the cwp cluster between cwp66 and slpA [14] (Figure 1A).

Figure 1.

Density of polymorphism in the cwp cluster and phylogeny of whole genomes and S-layer. A, Genetic organization in and around the cwp cluster. B, Density of polymorphism across the cwp cluster. C, Phylogeny constructed from the whole genomes. Solid black shapes indicate the clades. D, Phylogeny constructed from the slpA gene. Shapes indicate the clade, and colors indicate the S-layer variant with the exception of 2 hybrids, designated H and indicated by a star. Numbers indicate bootstrap support. Abbreviation: ORF, open reading frame.

Meaningful investigation of the diversity and evolution of bacterial antigenic determinants requires the rational choice of representative isolates. This is facilitated by combining molecular epidemiology and clinical phenotype data with population structure information [23]. We used this approach to select isolates for detailed genomic analysis [3] to discover the extent of cwp cluster genetic diversity and investigate how the cwp cluster evolves within the species.

METHODS

Isolates and Genotyping

Isolates were cultured from C. difficile positive stool samples identified by enzyme immunoassay (EIA; Premier Toxins A&B Enzyme Immunoassay; Meridian Bioscience Europe, Milan, Italy) at the Clinical Microbiology Laboratory, Oxford University Hospitals NHS Trust, Oxford, and by cytotoxin testing at the Leeds Teaching Hospitals NHS Trust, Leeds. A total of 1001 Oxford isolates were cultured between 16 September 2006 and 6 August 2010, and 84 Leeds isolates cultured between 12 October 2006 and 12 March 2008, together with five additional PCR-ribotype reference isolates were included (Table 1). Primary culture and genotyping by multilocus sequence typing (MLST) and PCR-ribotyping were performed as described elsewhere [24]. The notation ST1[4] was adopted to indicate ST1[S-layer cassette variant], and ST1(027) was adopted to indicate ST1 (PCR ribotype).

Table 1.

Isolates, Genotypes, and EMBL Short Read Archive (SRA) Sample Numbers

	Genotype							SRA Sample No.
Genome ID	ST	S-Layer	Clade	PCR Rib	Tox	Isolate ID	Isolation Date
0090	1	4	2	027	+	Ox160	29 Jan 2007	ERS139371
0098	2	10	1	020	+	Ox709	26 Sep 2007	ERS139373
6417	2	12	1	014	+	Ox1475	6 Sep 2008	ERS139420
6019	3	1	1	305	+	Ox428	14 Jun 2007	ERS139415
0193	3	4	1	001/072	+	Ox1867	13 Apr 2009	ERS139380
0551	3	8	1	262	−	Ox1003	23 Jan 2008	ERS139388
0039	4	7	1	137	+	Ox1145	20 Mar 2008	ERS139368
5010	5	10	3	069	+	Ox2183	18 Oct 2009	ERS139411
0568	5	11	3	023	+	Ox1523	26 Sep 2008	ERS139391
0034	6	11	1	005	+	Ox247	12 Mar 2007	ERS139367
0561	7	5	1	026	+	Ox1437a	14 Aug 2008	ERS139389
0117	8	9	1	002	+	Ox1192c	14 Apr 2008	ERS139374
0096	10	4	1	015	+	Ox660	11 Sep 2007	ERS139372
2448	11	3	5	033	+	L033a	7 Jun 2008b	ERS139399
2471	11	8	5	066	+	7721734	24 Nov 2009	ERS139402
2490	11	8	5	045	+	L045a	7 Jun 2008b	ERS139405
1729	11	H2/6	5	078	+	Ox575	14 Aug 2007	ERS139395
2387	11	H2/6	5	193	+	L16/26	19 Oct 2006	ERS139396
0562	12	1	1	003	+	Ox1424	1 Aug 2008	ERS139390
0149	13	10	1	129	+	Ox1533	1 Oct 2008	ERS139376
0160	14	6	1	014	+	Ox1463	27 Aug 2008	ERS139377
5172	15	12	1	010	−	Ox1342	10 Jun 2008	ERS139412
4139	16	2	1	029	+	Ox858	30 Nov 2007	ERS139409
6483	16	11	1	050	+	Ox590	30 Oct 2008	ERS139421
0143	17	6	1	018	+	Ox1192e	14 Apr 2008	ERS139375
1506	22	11	3	023	+	Ox561	7 Aug 2007	ERS139393
6282	23	10	4	138	−	Ox904	18 Dec 2007	ERS139416
2431	32	9	2	153	+	L28/45	31 May 2007	ERS139397
0182	35	3	1	284	+	Ox1121	9 Mar 2008	ERS139379
2958	36	4	1	011	+	Ox1916	22 May 2009	ERS139407
4350	36	8	1	011	+	Ox2553	7 May 2010	ERS139410
0089	37	7	4	017	+	Ox920	26 Dec 2007	ERS139370
6346	39	2	4	085	−	L085a	7 Jun 2008b	ERS139418
0224	41	4	2	106	+	Ox1307	30 May 2008	ERS139382
1728	41	5	2	194	+	Ox2287	10 Dec 2009	ERS139394
2439	41	10	2	321	+	Ox1802b	28 Feb 2009	ERS139398
0175	42	10	1	106	+	Ox687	19 Sep 2007	ERS139378
0516	43	11	1	054	+	Ox1844	28 Mar 2009	ERS139385
0477	44	5	1	015	+	Ox990	21 Jan 2008	ERS139383
0024	44	9	1	015	+	Ox466	6 Jul 2007	ERS139366
5740	45	1	1	454	+	Ox2294	15 Dec 2009	ERS139413
0061	45	10	1	013	+	Ox887	12 Dec 2007	ERS139369
5984	47	11	2	375	+	Ox2621b	17 Jun 2010	ERS139414
6353	48	7	1	038	−	Ox2167	12 Oct 2009	ERS139419
6325	49	10	1	014	+	Ox593	14 Aug 2007	ERS139417
0526	54	1	1	012	+	Ox1567	24 Oct 2008	ERS139386
2479	54	7	1	012	+	Ox2478	26 Mar 2010	ERS139403
CD630	54	7	1	012	+	CD630	1982	NC009089
0529	54	8	1	012	+	Ox1396	16 Jul 2008	ERS139387
0509	58	8	1	056	+	Ox707	26 Sep 2007	ERS139384
1463	59	3	1	316	+	Ox1893	4 May 2009	ERS139392
2482	63	1	1	053	+	Ox1918	25 May 2009	ERS139404
2975	66	11	1	022	+	Ox2124	11 Sep 2009	ERS139408
2493	67	7	2	019	+	Ox2163	7 Oct 2009	ERS139406
0197	77	11	1	011	+	Ox2017	22 Jul 2009	ERS139381
2460	95	11	2	075	+	L075a	7 Jun 2008b	ERS139401
2452	96	11	3	058	+	L058a	7 Jun 2008b	ERS139400
6877	160	11	1	015	+	L86/78	27 Feb 2009	ERS139422

The project Web site is available at: http://www.ebi.ac.uk/ena/data/view/ERP001417.

Abbreviations: ID, identification; L, Leeds; Ox, Oxford; PCR Rib, polymerase chain reaction ribotype; ST, sequence type; Tox, toxigenic; –, negative; +, positive.

^a PCR-ribotyping reference library isolate.

^b Date received at Leeds laboratory.

DNA Sequencing

DNA was extracted from bacterial cells that had been cultured anaerobically on Columbia blood agar for 48 hours at 37°C, using commercial kits (FastDNA, MP Biomedicals, CA; QuickGene, Fujifilm Europe, Dusseldorf, Germany; or QIAamp, Qiagen, Hilden, Germany). DNA was sequenced using Illumina (San Diego, CA) sequencing-by-synthesis technology [3], frequently referred to as “next-generation DNA sequencing.” A combination of standard Illumina and in-house protocols were used to produce multiplexed paired-end libraries with an average insert size of approximately 200 bp. Twelve-plex pooled libraries were sequenced on the Genome Analyzer II (GAII) or GAIIx platforms to produce 51 bp or 100–108 bp reads, respectively, and 96-plex pooled libraries were sequenced on the HiSeq2000 platform to produce 99 bp or 100 bp paired reads.

De Novo Assembly of Sequence Data

All genomes were assembled de novo using Velvet [25]. Velvet Optimiser was used to determine optimal parameter values. Assemblies had an average of 703 contigs. We assembled the genomes de novo, without using a reference genome template, so that insertions and deletions would not be missed and regions of high genetic diversity would be assembled correctly.

Analysis of Whole-Genome and Partial-Genome Sequences

A total of 57 isolates were chosen for detailed phylogenetic analysis; they represented the 5 clades of the C. difficile population structure and a range of recognized clinical phenotypes [10–12, 23]. A whole-genome Neighbor-joining tree was constructed as follows, on the basis of de novo sequence assemblies. BLAST was used to search the 57 genomes for 3742 genes previously annotated in CD630 [14]. A total of 1639 of these genes were found to be present (with ≥90% sequence coverage) in all 57 genomes, and these sequences were used to build the tree (Figure 1C).

The entire de novo genome assemblies were uploaded into a Bacterial Isolate Genome Sequence Database (BIGSdb) [26]. BIGSdb allows simultaneous BLAST searching of user-defined loci in the genome assemblies of multiple isolates. In this way, open reading frames (ORFs) of interest, such as slpA, were tagged, extracted, and then aligned using ClustalW [27]. Neighbor-joining trees were then constructed from this alignment, using MEGA version 4 [28].

The 24-kb insertion of S-layer cassette 11 was translated using BioEdit Sequence Alignment Editor [29] and Artemis genome browser and annotation tool [30]. A BLAST search of the predicted translation products against GenBank was used to identify related proteins, thus predicting functions of the ORFs and the species in which they occurred (Table 2).

Table 2.

Predicted Functions of Proteins Encoded by 19 Open Reading Frames (ORFs) of the Putative S-Layer Glycosylation Gene Cluster

ORFa (nt)	Gene	Putative Function	Closest Species Match	GenBank Accession No.	Amino Acid (%)		GC Content (%)
					Identity	Similarity
1 (408)	…	Hypothetical protein	Clostridium difficile	ZP_05400366.1	57	84	29.9
2 (1395)	…	Undecaprenyl-phosphate glucose phosphotransferase	Clostridium lentocellum	YP_004310697.1	57	74	23.9
3 (969)	…	Glycosyl transferase	Lachnospiraceae bacteria	ZP_08602110.1	56	75	24.8
4 (891)	…	Phosphoribose diphosphate: decaprenyl-phosphate phosphoribosyltransferase	C. difficile	YP_001087463.1	65	81	24.5
5 (1797)	…	Hypothetical protein	Tolumonas auensis	YP_002893223.1	26	45	26.2
6 (1332)	…	Glycosyl transferase	Xanthomonas perforans	ZP_08189725.1	49	65	26.6
7 (3486)
N-terminus	…	Multidomain glycosyl transferase	Bacteroides species	ZP_08584442.1	32	54	26.3b
C-terminus	…	Multidomain glycosyl transferase	Polynucleobacter necessarius	YP_001155105.1	51	68	26.3b
8 (1161)	…	Glycosyl transferase	Aromatoleum aromaticum	YP_157889.1	50	65	28.7
9 (1383)	…	Glycosyl transferase	Clostridium beijerinckii	YP_001311811.1	34	58	22.4
10 (909)	…	Glycosyl transferase	C. beijerinckii	YP_001311812.1	67	81	22.4
11 (1283)	wzt	ATP binding cassette (ABC) transporter: ATPase	C. beijerinckii	YP_001311813.1	65	81	26.6
12 (789)	wzm	ABC transporter: permease	Eubacterium yurii	ZP_07454366.1	68	84	25.6
13 (1023)	rmlBc	dTDP-glucose 4,6-dehydratase	Turicibacter species	ZP_08166203.1	73	88	27.7
14 (573)	rmlCc	dTDP-4-dehydrorhamnose 3,5-epimerase	Clostridium perfringens	ZP_02863393.1	72	86	28.0
15 (924)	…	Phosphogluconolactonase; provisional	Lachnospiraceae bacteria	ZP_08605193.1	34	59	25.4
16 (879)	rmlAc	Glucose-1-phosphate thymidylyltransferase	Turicibacter species	ZP_08166199.1	83	93	30.3
17 (681)	rmlDc	dTDP-4-dehydrorhamnose reductase	C. difficile	ZP_05328363.1	69	86	27.2
18 (816)	rfbNc	Rhamnosyltransferase	Thermoanaerobacter pseudethanolicus	YP_001665609.1	50	70	25.5
19 (1608)	wzyC	O-Antigen polymerase/ligase	Geobacillus thermoglucosidasius	YP_004586423.1	33	54	23.2

C. difficile was found as the closest species match to 3 ORFS. However, although the low level of amino acid identity indicates a similar function for the ORF (eg, an alternative rhamnose pathway in the case of rmlD), the 3 ORFs were widely dispersed in the CD630 reference genome [14]. Thus, these low-level matches do not indicate the presence of another putative S-layer glycosylation cluster. Putative functions of the predicted ORFs were inferred using the entire results of the BLAST query, rather than just the closest match shown in Table 2.

Abbreviations: nt, nucleotide; ORF, open reading frame.

^a Numbered as in Figure 3.

^b Includes both the N-terminus and C-terminus species matches.

^c Rhamnose pathway.

The Artemis Comparison Tool (ACT) [31] was used to represent the relative position of the genes in the reference genome CD630 [14] and in a genome containing the glycosylation cluster (Figure 3).

Figure 3.

Annotation of the putative S-layer glycosylation cluster within ST5 relative to the reference genome CD630 [14]. The annotation of CD630 is shown at the top, and the location of each CD630 gene in the ST5 genome is shown using grey blocks. Color has been used to highlight the glycosylation cluster insertion, the rearrangement of the 2 flanking open reading frames (ORFs), and the deletion of cwp2. Annotation of the genes in the glycosylation cluster is given at the bottom. Numbers 1–19 indicate the ORFs of the glycosylation cluster as in Table 2.

Analyses Using a Reference-Anchored Multiple Alignment

Each de novo assembled genome was aligned separately against the reference genome CD630 [14] by using progressive Mauve [32], and reference-anchored alignments were extracted and combined to produce a multiple-way alignment of all genomes, in which each alignment column corresponded to a genomic position of CD630. The density of polymorphic sites in the part of this alignment corresponding to the cwp cluster of CD630 was computed. Distributions of polymorphisms between pairs of isolates were plotted along the whole CD630 genome, using DNAplotter [33] (Figure 4A), and around the cwp cluster (Figure 4B). Ratios of nonsynonymous-to-synonymous mutations (dN/dS) were calculated for selected genes of the cwp cluster on the basis of the reference-anchored alignment, using the method of Nei and Gojobori [34].

Figure 4.

S-layer switching at the chromosomal scale and at the scale of the cwp cluster. A, Whole-genome distributions of polymorphism between pairs of isolates very closely related in terms of whole-genome phylogeny (Figure 1C) but with distinct S-layer cassettes (Figure 1D and Figure 2A and 2B). The 2 outer rings composed of small red lines indicate the open reading frames (ORFs) annotated on the forward and reverse strands of reference genome CD630 [14]. The left-hand plot shows, from inside out, pairs ST10[4]/44[5], ST54[8]/54[1], and ST14[6]/49[10]; the middle plot shows, from inside out, ST41[5]/41[10], ST11(078)[H]/ST11(033)[3], and ST11(078)[H]/ST11(066)[8]; and the right-hand plot shows, from inside out, ST2[10]/ST2[12],ST36[4]/ST36[8], and ST160 [11]/ST44[5]. Blue highlighting indicates the location of the cwp cluster within the chromosome. B, Distribution of polymorphism between the pairs of genomes shown in (A) within the region of the genome containing the cwp cluster. By enlarging and comparing only the region of the cwp cluster involved in S-layer switching (shown in blue in panel A), the distribution of polymorphisms can be used to estimate the size of recombination events. Each row represents a pairwise comparison of 2 isolates, and polymorphisms are shown in red. Abbreviation: SNV, single nucleotide variant.

Nucleotide Sequence Accession Numbers

The 57 genomes that underwent detailed phylogenetic analysis (Table 1) were submitted to the EBI short read archive under the project accession number ERP001417, available at http://www.ebi.ac.uk/ena/data/view/ERP001417. Accession numbers for individual genomes are listed in Table 1. The annotated DNA sequence containing the putative S-layer glycosylation gene cluster (Figure 3) was submitted to EMBL (accession number HE980331).

Ethics Statement

This study included bacterial isolates for which no corresponding patient data were used. However, the isolates were collected without written informed consent as part of a larger study of C. difficile transmission across the health economy, for which ethical permission was obtained from the Berkshire Ethics Committee (10/H0505/83) and the UK National Information Governance Board (8–05(e)/2010).

RESULTS

Choice of Isolates and Genomes

Whole-genome sequences (WGS) were available for 1085 recent clinical isolates (1001 from Oxford and 84 from Leeds) and 5 PCR-ribotype reference isolates (Table 1). Genotyping was performed by MLST; the sequence types (STs) were determined by conventional MLST [23, 24] or were extracted from WGS using BIGSdb [26]. STs were consistent by both methods. The slpA gene of each isolate was also extracted from WGS by using BIGSdb, or it was identified from its genetic context within the cwp cluster if it was genetically divergent from known sequences (Figure 1A) [14].

The genotype and slpA sequence data were used to choose 57 isolates for detailed phylogenetic study (Table 1). Isolate choice was based on 2 considerations. First, isolates were chosen to represent known characteristics of different genotypes, including the spectrum of virulence and clinical prevalence [11, 12, 35, 36] and their evolutionary context within the C. difficile population structure [23]. Second, if a ST occurred with >1 highly genetically divergent slpA variant, a representative of each combination was included. Hence, 6 STs with 2 highly divergent slpA variants and 4 STs with 3 slpA variants were included (Table 1).

cwp Cluster Genetic Diversity

The diversity of the cwp cluster and flanking region (total, 63.5 kb; Figure 1A) was examined using a nucleotide sequence alignment generated from the 57 isolates and reference strain CD630 [14]. Diversity peaked across the central approximately 10 kb, which included cwp66, secA2, and slpA (Figure 1B). The ratio of nonsynonymous to synonymous point mutations (dN/dS) was equal to 1.03 in the outer LMW fragment of the S-layer protein, indicating a strong relaxation of the purifying selection at work elsewhere in the genome.

Phylogenetic Relationships

The phylogeny of the 58 isolates based on the core genome (genes common to all) showed the same 5 clades of the population structure as determined using MLST data (Figure 1C) [23]. This structure was also preserved in genes flanking the cwp cluster. However, with increasing proximity to the cwp66, secA2, and slpA genes, an entirely different interstrain relationship emerged. A neighbor-joining tree for the slpA gene of the 57 isolates and CD630 identified 12 distinct clusters (Figure 1D), rather than the usual 5 clades. Furthermore, neighbor-joining trees for the cwp66 adhesin and secA2 translocase clustered these 58 isolates identically to slpA (Figure 2A and 2B). These data suggest that slpA, cwp66, and secA2 coevolve as an approximately 10-kb gene cassette, which has at least 12 genetically divergent variants. Most variants of this S-layer cassette occurred in multiple clades, indicating independent dispersal of the cassette throughout the C. difficile population by frequent horizontal genetic exchange. Only 2 isolates (ST11(078) and ST11(193)) contained a hybrid cassette comprising the cwp66 gene of one cassette and the secA2 and slpA genes of another (Figure 1D and Figure 2A and 2B). A comparison of cwp cluster sequences from 4 genomes (ST1(027), ST3(001), ST37(017), ST54(012)) with older isolates of the same ST and S-layer cassette [14, 37] indicated a very low rate of point mutation accumulation over time.

Figure 2.

Phylogeny of cwp66 and secA2. A and B, Phylogeny constructed from cwp66 (A) and secA2 (B). Shapes indicate the clade of each genome (Figure 1C). S-layer cassette variants are shown using colors, with the exception of 2 hybrids, indicated by a star. Numbers indicate bootstrap support.

Glycosylation Gene Cluster

A novel insertion of 23.8 kb containing 19 predicted ORFs was identified within one of the S-layer cassettes (variant 11, associated with 11 STs; Figure 3). The insertion represented a putative S-layer glycosylation gene cluster, encoding enzymes required to initiate, extend membrane translocate and ligate a glycan chain to a substrate molecule (Table 2). These components are typical of the 4 S-layer glycosylation gene clusters described to date, which are found in nonpathogenic Gram-positive bacilli [15]. No such clusters have been described in Clostridium species. The putative C. difficile S-layer glycosylation cluster exhibited detectable amino acid sequence homologies with 2 of the Bacillus species S-layer glycosylation gene clusters (Supplementary Figure 1) [15].

The order of 2 cwp cluster genes flanking the 23.8-kb insertion (cwp66 and CD2790) was reversed, and the gene cwp2 was deleted (Figure 3), bringing together the 3 genes (cwp66, secA2, and slpA) of the S-layer cassette. The slpA gene of cassette 11 was also uniquely short, at 611 amino acids, compared with 720 amino acids for CD630. Cassette 11 occurred in 3 different clades (1, 2, and 3), indicating that horizontal genetic exchange had occurred involving a DNA fragment at least 34 kb containing cwp66, secA2, slpA, and the associated glycosylation cluster.

Scale of Recombination Events

The uniqueness and scale of the recombination events causing S-layer cassettes to be exchanged were visualized at the chromosome level for selected pairs of isolates (Figure 4A). By comparing the polymorphisms between the cwp clusters of these otherwise closely related pairs, the size of the recombination events was inferred as 12.9–35.2 kb (Figure 4B). A region of approximately 12 kb containing the S-layer cassette was identified, which remained unbroken (Figure 4B). This is consistent with the congruence of neighbor-joining trees for cwp66, secA2, and slpA (Figure 1D), further supporting the genetic coevolution of these loci as 12 independently reassorting S-layer cassettes.

DISCUSSION

Although evolutionary changes in immunodominant cell surface antigens are likely critical to host-pathogen interactions, the extremely high level of genetic polymorphisms in the C. difficile slpA and cwp66 genes has precluded large-scale population-wide comparisons by conventional Sanger sequencing. We have overcome this limitation by using newly available DNA sequencing methods [3] to determine whole pathogen genome sequences. These data have confirmed the existence of 5 clades in C. difficile and identified 12 stable variants of the approximately 10-kb S-layer cassette. The cassettes contain the highly diverse (Figure 1B) and functionally interrelated slpA, cwp66, and secA2 genes [6, 7, 22]. Unexpectedly, the clades and S-layer cassettes associated randomly, effectively behaving as independent components of the genome in linkage equilibrium (Figure 1). The underlying mechanism is the genetic replacement of one S-layer cassette with another by homologous recombination involving DNA fragments of 12–35 kb (Figure 4). We refer to this process as S-layer switching because it parallels polysaccharide capsular switching in other bacterial species [1, 2]. Both S-layer and capsular switching result in major antigenic shifts, while the remainder of the genome is unchanged.

The extreme genetic diversity between S-layer cassettes contrasts with the low rate of point mutation accumulation within each cassette, with isolates of the same variant showing very little diversity. These observations are consistent with well-established mathematical models of strong immune selection [20], which predict that the collective immune responses of the host population shape pathogen antigenic diversity into nonoverlapping, independently transmitted antigenic types. Such models predict that intermediate antigenic types that cross-react serologically will be lost from the population through competitive exclusion. The high diversity of the slpA and cwp66 genes and higher dN/dS ratio for the LMW S-layer domain are consistent with this region being under intense diversifying selective pressure. In addition to host immunity, the high selective pressure may also reflect the need for successful strains to avoid bacteriophage attack [38].

An interesting question is whether there is any evidence of association between S-layer cassette and hypervirulent phenotype. We found that the S-layer cassettes of ST1(027) (a major hypervirulent strain identified in 2005 [11]) and ST3(001) (a previous United Kingdom epidemic strain [39]) were very closely related (Figure 1D), consistent with previous reports [36]. However, this S-layer cassette also occurred in a third clinically abundant genotype, ST10(015), and in 2 clinically rare genotypes (Figure 1D, and Figure 2; unpublished data) [35]. The fact that 3 clinically important genotypes share closely related S-layer cassettes suggests that the hypervirulence of ST1(027) may be influenced but not solely conferred by this feature. The S-layer cassette of the more recently identified hypervirulent ST11(078) [12] is noteworthy since it represents the only example of a hybrid cassette; its cwp66 gene is homologous to cassette 2 cwp66, and its slpA and secA2 genes are similar to those of cassette 6 (Figure 1D and Figure 2). On the basis of nucleotide sequence data, this hybrid would be predicted to cross-react immunologically with its 2 parent cassettes [7, 19]. This contradicts model predictions [20] that cross-reactive variants should be removed from the population by competitive exclusion. The hybrid was also found in clinically rare ST11(193) [35], which may have evolved from ST11(078) (Figure 1C). Its separate cwp66 and secA2/slpA elements were closely related to variants found in nonhypervirulent STs (Figure 1D and Figure 2A and 2B), arguing against a role for the hybrid cassette in the hypervirulent phenotype of PCR-ribotype 078. However, the recombination affecting the ST11(078) S-layer cassette seems to have occurred relatively recently because the chromosomes of the ST11 genomes showed few differences outside this region (Figure 4). This recombination may be coincident with the emergence of ST11(078) as a causative agent of severe CDI. Overall, our data do not exclude the possibility that S-layer variants can affect clinical phenotype.

This study contradicts previous smaller studies suggesting that traditional genotyping predicts antigenic type [36, 40]. By including a large number of genomes (1090, of which 1085 were from recent clinical isolates) in our initial screen, we were able to demonstrate that isolates sharing the same ST and PCR-ribotype can carry multiple distinct S-layer cassettes. For example, PCR-ribotype 015 was found in association with 4 different S-layer cassettes, and 4 STs (ST3, ST11, ST41, and ST54) occurred with 3 different S-layer cassettes (Figure 1 and Table 1). This demonstrates that the rate of S-layer switching exceeds the rate at which new genotypes (as defined by PCR ribotype or ST) are generated. It also establishes conclusively that genotype is an unreliable predictor of antigenic type. Our observations have important implications for the way in which isolates and subsequently antigens are identified for potential inclusion in C. difficile vaccines and for the development of C. difficile phage therapy [41].

The use of de novo assembled sequences in this study (rather than reference-based assemblies) revealed an unexpected insertion of approximately 24 kb in one S-layer cassette (variant 11). Its 19 ORFs were predicted to encode all of the components that characterize an S-layer glycosylation cluster (Figure 3) [15], including a rhamnose biosynthesis pathway [42]. This sugar is unique to bacteria and therefore represents an attractive drug target. The genes flanking cassette 11 were swapped, bringing together the 3 genes cwp66, secA2, and slpA (Figure 3). The 19 ORFs of the insertion were present and intact in all 11 STs in which it was found, which represented 3 of the 5 clades. This suggests that its approximately 34-kb sequence participates in S-layer switching as a single genetic element (Figure 4). S-layer cassette 11 is so unusual that it may have originated in a distinct and as yet unidentified species and then incorporated into the C. difficile chromosome by interspecies recombination. This is the first description of a putative S-layer glycosylation gene cluster in a Gram-positive human pathogen or in any Clostridium species. It may significantly alter the characteristics of the outer cell surface, with potentially important effects on antigenicity, antibiotic permeability, and virulence.

Our findings demonstrate the novel insights to be gained by exploiting WGS for the cross-population analysis of important bacterial pathogens. Knowledge of the evolutionary process of S-layer switching could help explain temporal changes and geographic differences in the epidemiology of CDI [35, 43] and will potentially influence future genotyping schemes, as well as therapeutic and vaccination strategies. Further insights into the impact of C. difficile evolution on the epidemiology of this clinically important human pathogen will require longitudinal isolate collections from different geographical areas, concomitant with changes in incidence and the clinical severity of CDI.

Supplementary Data

Supplementary materials are available at The Journal of Infectious Diseases online (http://jid.oxfordjournals.org/). Supplementary materials consist of data provided by the author that are published to benefit the reader. The posted materials are not copyedited. The contents of all supplementary data are the sole responsibility of the authors. Questions or messages regarding errors should be addressed to the author.