Optimization of Pulsed-Field Gel Electrophoresis Protocols for Salmonella Paratyphi A Subtyping

Abstract

Salmonella enterica serovar Paratyphi A infection has caused public health problems in some countries in recent years. Pulsed-field gel electrophoresis (PFGE) has been used for the subtyping and epidemiological investigations of some serotypes of Salmonella, mainly in outbreaks caused by non-typhoidal Salmonella. In this study, different restriction endonucleases and electrophoresis parameters were compared for the PFGE subtyping by using Salmonella Paratyphi A strain panels. Two protocols for the enzymes SpeI and XbaI showed higher discriminatory power, which may facilitate epidemiological analysis for more accurate case definition, and clonality study of Salmonella Paratyphi A.

Introduction

S almonella enterica serovar Paratyphi A is a human-restricted bacterial pathogen within the Salmonella serovars. It has been estimated that 5.4 million cases of paratyphoid fever occur annually worldwide (Crump et al., 2004). During the past decade, outbreaks of paratyphoid fever due to Salmonella Paratyphi A have been reported in several countries, especially in East and South Asia (Ochiai et al., 2005; Jin, 2008). In India, the first paratyphoid fever outbreak was reported in 1996, and infections have been increasing since then (Kapil et al., 1997; Thong et al., 1998; Sood et al., 1999; Gupta et al., 2009). In China, outbreaks of paratyphoid fever have occurred in Jiangxi and Guangxi provinces since 1995, and Salmonella Paratyphi A has experienced a dramatic increase and has replaced Salmonella Typhi as the dominant serovar of enteric fever in some provinces (Yan et al., 2005; Jin, 2008).

The genotyping of bacterial pathogens is important for surveillance, epidemiological investigations, and outbreak detection. Pulsed-field gel electrophoresis (PFGE) has been successfully used for the characterization of some Salmonella serotypes (Li et al., 2005; Dionisi et al., 2006; Seo et al., 2006; Kam et al., 2007; Soyer et al., 2010). A standardized PFGE protocol is used by the subtyping laboratory surveillance network, PulseNet (Swaminathan et al., 2001). The protocol used for the subtyping of Salmonella serotypes (previously for non-typhoidal Salmonella) is publically available (http://www.pulsenetinternational.org/protocols/Pages/default.aspx).

During our surveillance of Salmonella Paratyphi A, limited patterns were obtained when the strains from multiple years and multiple provinces were analyzed with the standard protocol used for Salmonella serotypes (Li et al., 2006). Therefore, it was unclear whether this protocol has limited discriminatory power for the Salmonella Paratyphi A isolates or whether there was a nationwide outbreak that spanned many years and provinces. In addition, it is known that Salmonella Paratyphi A infection may have a longer (more than 1 week) preclinical period than other foodborne infections, which may be a disadvantage during outbreak investigations, because this makes it more difficult to determine exposure factors and to perform source tracing.

As Salmonella Paratyphi A is currently an important public health hazard, in this study we compared several new PFGE protocols based on the PulseNet 1-day standardized PFGE protocol for the subtyping of Salmonella serotypes. The new protocols can enhance the discriminatory power for Salmonella Paratyphi A PFGE subtyping and can be used as supplementary subtyping protocols in the epidemiological analysis, if more refined subtyping is needed for case definition and source tracing.

Methods

Salmonella Paratyphi A strains

Three strain panels were used for the evaluation of the PFGE protocols. The first panel included 11 strains isolated from different years and provinces in China (Suppl. Table S1; Supplementary Material is available online at www.liebertonline.com/fpd) to potentially represent epidemiologically unrelated infections and was used for the comparison of the 10 electrophoresis parameters. The second panel of 33 strains isolated from different years and provinces (Suppl. Table S1) was used as the test strains to compare the protocols (three for each enzyme) for their discriminatory power. The third panel of 106 strains from epidemic years (1998–2010) and 12 provinces (Fig. 1) was further selected randomly from our collection to evaluate the protocol and also to retrospectively analyze the characterization of the Salmonella Paratyphi A strains isolated in China. The serotype was identified using Salmonella antisera (S&A, Bangkok, Thailand) according to the White-Kauffmann-le Minor scheme (Grimont and Weill, 2007). Salmonella Braenderup strain H9812 was used as a DNA size marker as recommended (Hunter et al., 2005).

FIG. 1.

The pulsed-field gel electrophoresis (PFGE) patterns of XbaI (1.5–29 s, 20 h) and SpeI (1–20 s, 20 h), and the combination of the two enzymes used for the panel of 106 strains. The strains with different XbaI patterns are separated by thick lines, and the strains with different SpeI patterns within one XbaI pattern are separated by the thin lines.

Selection of restriction endonucleases

The frequencies of the restriction sequences in the whole genome of Salmonella Paratyphi A strain ATCC 9150 (GenBank NC_006511) and the theoretical DNA fragments generated were analyzed using the SeqBuilder program of the Lasergene6 software package (DNASTAR, Inc., Madison, WI) with its built-in 247 enzymes. The enzymes where most of the restriction fragments were larger than 20.5 kb and the number of fragments more than 20.5 kb was 10–50 were selected and used in the optimization of the PFGE protocols.

Optimization of the electrophoretic parameters

A two-stage electrophoresis parameter optimization was performed. For each restriction enzyme selected, a pilot study was done with the first panel of 11 isolates and 10 different electrophoresis parameters, including the PulseNet 1-day standardized PFGE protocol for the subtyping of Salmonella serotypes, and those recommended by the CHEF Mapper software program based on the sizes of the restriction fragments. Some of the parameters were then subsequently modified to better distinguish the bands. For each enzyme, three sets of parameters were finally selected for extensive evaluation using the second strain panel (33 strains, the second optimization stage). The D value was used to estimate the discriminatory power of PFGE with different electrophoresis parameters and enzymes, which was developed based on Simpson's index of diversity (Hunter and Gaston, 1988).

PFGE

The PFGE protocols were based on PulseNet 1-day standardized PFGE protocol for the subtyping of Salmonella serotypes, and the enzymes and electrophoresis parameters may change for the comparisons.

PFGE patterns analysis

The DNA patterns were analyzed using BioNumerics (version 5.1; Applied Maths, Sint-Martens-Latem, Belgium). The similarity coefficient was calculated using the Dice method. The band tolerance used for the comparison of pattern profiles was 1%. The cluster analysis was done by unweighted pair groups with arithmetic averages (UPGMA). The fragments smaller than 20.5 kbp were not analyzed. Each PFGE pattern differing by at least one band from a previously recognized type was considered to be a new pattern. Each unique PFGE pattern was assigned a pattern name.

Results

Selection of restriction enzymes and electrophoresis parameters using the first strain panel

XbaI, SpeI, BlnI (Avr II), XhoI, PsPXI, and SanDI were selected based on the criteria described in Methods. PsPXI and SanDI were eliminated from our analysis because of their rarities and high prices. Among the four remaining enzymes, XbaI, SpeI and BlnI (AvrII) were already being used in the PulseNet 1-day standardized PFGE protocol for the subtyping of Salmonella serotypes. In theory, the four enzymes should digest the genomic DNA of Salmonella Paratyphi A ATCC 9150 into 31, 38, 18, and 51 fragments, respectively. After excluding fragments smaller than 20.5 kb, the fragment numbers for digestion with these enzymes should be 27, 32, 17, and 34, respectively.

For each selected restriction enzyme, a pilot study was done with the first panel of 11 isolates and using 10 different electrophoresis parameters (data not shown). Then, for each enzyme, three sets of parameters (named a, b, and c; Table 1) were selected for further comparisons with the second strain panel. Parameter a exhibited the highest discriminatory power for fragments larger than 310.1 kb, and parameter c exhibited strong discriminatory power for fragments smaller than 310.1 kb. Parameter b provided the maximum overall resolution for all fragments. Among these parameters, X-a and B-a (XbaI and BlnI, parameter a) were also recommended by the PulseNet 1-day standardized PFGE protocol.

Table 1.

Candidate Electrophoresis Parameters Using the Selected Enzymes and Their Discriminatory Power for the Panel of 33 Strains

Enzyme	Electrophoresis parameter	Switch times	Run time	Pattern number ^a	D values ^a
XbaI	X-a	2.2–63.8 s	20 h	16	0.764
	X-b	1–40 s	20 h	15	0.828
	X-c	1.5–29 s	19 h	17	0.877
SpeI	S-a	1–30 s	20 h	22	0.938
	S-b	20–29 s for 8 h, 1–13 s for 12 h	20 h	22	0.960
	S-c	1–20 s	20 h	23	0.964
XhoI	Xh-a	2.2–29 s	20 h	16	0.881
	Xh-b	2.2–2.8 s for 4 h, 7.6–20.9 s for 16 h	20 h	15	0.876
	Xh-c	2.2–18 s	20 h	16	0.881
BlnI (AvrII)	B-a	2.2–63.8 s	20 h	11	0.633
	B-b	5–50 s	20 h	ND	ND
	B-c	2.2–63.8 s for 14 h, 1.7–8.3 s for 6 h	20 h	ND	ND

The number of patterns and the D values for each electrophoresis parameter were both generated with the second panel of 33 strains.

Evaluation of restriction enzymes and electrophoresis parameters using the second strain panel

The strains of the second panel were digested with XbaI, SpeI, BlnI (AvrII), and XhoI, respectively, and PFGE was run with the different electrophoresis parameters listed in Table 1. Clustering of the PFGE patterns was performed with BioNumerics (Suppl. Figs. S1–4). The number of patterns and the D values were obtained for the different enzymes and electrophoresis parameters (Table 1). For XbaI, parameter X-c provided the most patterns at the 100% similarity breakpoint and had the highest D value. In the SpeI-PFGE analysis, S-c resulted in the most patterns and the highest D values compared to the other two parameters. For XhoI, the D values of Xh-a and Xh-c were the same, and were higher than for Xh-b. However, when these patterns were clustered with UPGMA, Xh-a and Xh-c yielded five and four clusters at 95% similarity, respectively. Therefore, we deduced that Xh-a has the highest discriminatory power for this panel of strains.

When these 33 strains were analyzed with BlnI PFGE with the B-a parameter, only 11 patterns were obtained, and the D value was only 0.633 (Suppl. Fig. S4). Since BlnI-PFGE generated the fewest patterns out of the above three enzymes, BlnI was not included in the subsequent analyses.

When different enzymes were compared, SpeI-PFGE had the highest discriminatory power (0.964 with the electrophoresis parameter S-c) (Table 1), which also had much higher discriminatory power than the standardized XbaI-PFGE and BlnI-PFGE protocols for the subtyping of Salmonella serotypes. A new XbaI electrophoresis parameter, X-c, also showed a higher discriminatory capacity than the standardized XbaI-PFGE protocol for the subtyping of Salmonella, and had a similar D value to Xh-a using XhoI. Therefore, SpeI with the S-c parameter was the first choice for the PFGE analysis of Salmonella Paratyphi A in this study, followed by X-c (using XbaI) or Xh-a (using XhoI) as the second choice. X-c generated more patterns than Xh-a when the second panel of 33 strains was analyzed. Therefore, protocols S-c and X-c were used in our further studies of PFGE with 106 isolates.

Evaluation of the optimized PFGE protocol and summary of the analysis of epidemic strains

A total of 106 isolates collected from 12 provinces between 1998, when there were a number of epidemics of paratyphoidal fever in China, and 2010, were selected for further evaluation using SpeI and XbaI (Fig. 1). With SpeI digestion and the S-c electrophoresis protocol, a total of 31 PFGE patterns were obtained. Each pattern was named JKPS18.CN000X according to the naming rules of the patterns in PulseNet. JKPS18.CN0002 was the most common pattern, which was associated with 33 isolates (31%), was present in all of the years except 1999, and included strains isolated in nine out of the 12 provinces. The second most frequently detected pattern was JKPS18.CN0001, which was present in 19 isolates (18%). This pattern was also present in all of the years except 1999 and was found in the isolates from five provinces. The third most common pattern, JKPS18.CN0029, which was present in nine out of 13 years included in the study and was distributed in six provinces, was identified for 15 isolates (14%). In addition, five different patterns were represented by two to four isolates each. The remaining 22 patterns were unique. The D value of SpeI for these strains was 0.852.

The number of patterns obtained with the X-c protocol using XbaI was 20 (Fig. 1). Each PFGE pattern obtained was named JKPX01.CN000X. The pattern JKPX01.CN0002 predominated and was contained in 47 of 106 isolates (44%). The second major pattern was JKPX01.CN0004 and was found in 23 isolates (22%). Two patterns (JKPX01.CN0001 and JKPX01.CN0005) were noted in eight isolates each. Another four patterns were represented by two isolates each, while the remaining 12 patterns were unique to specific isolates. The predominant JKPX01.CN0002 pattern was present in all years included in the study, and was distributed in seven out of the 12 provinces, while JKPX01.CN0004 was present after 2002 (2002–2010) and was distributed in nine provinces. The D value of XbaI subtyping was 0.750.

With the panel of 106 strains, SpeI digestion obtained more subtypes and higher D values than XbaI (Fig. 1). When the SpeI and XbaI patterns were combined, a total of 42 PFGE pattern combinations (from patterns COM1 to COM42) were obtained (Fig. 1 and Suppl. Fig. S5), and the D value increased to 0.920. Clustering generated with the combinations of SpeI and XbaI patterns showed complexity of the tree (Suppl. Fig. S5), whereas a predominant clone covering COM06, COM17, and COM07 had much similar PFGE patterns, suggesting that a conservative clone existed for more than 10 years and was widely spread. We compared the frequency distribution of the strain numbers in each pattern of individual XbaI and SpeI subtyping, using the combination of XbaI and SpeI (Fig. 2). The combination subtyping showed the most dispersive patterns within the 106 strains, as shown in Figure 2. The height of the “peak” was decreased, and the “tail of the peak” showed a significant right-shift, which indicated that it provided the highest subtyping ability for these 106 strains from different years and provinces. There were still some common patterns in the XbaI and SpeI combination subtyping. The most predominant, COM16 (JKPS18.CN0002/JKPX01.CN0004), which included 19 isolates, was present in 10 out of 13 years included in the study, and was distributed in seven provinces.

FIG. 2.

The frequency distributions of strains in the pulsed-field gel electrophoresis (PFGE) patterns of XbaI (1.5–29 s, 20 h) and SpeI (1–20s, 20 h), and those obtained using the combination of the two enzymes (XbaI+SpeI). The x-axis shows the PFGE patterns and is set to 42, the sum of the XbaI+SpeI combination patterns, for the subtyping comparison of the two individual enzymes and their combination. The y-axis indicates the sum of the strains for each pattern and is set to 50 for each subtyping method.

Discussion

In this study, several enzymes and various electrophoresis parameters were compared for the PFGE subtyping of Salmonella Paratyphi A. We previously noted that only a few subtypes were obtained in Salmonella Paratyphi A (Li et al., 2006) when typed using the PulseNet protocol for Salmonella serotypes. The protocols we developed herein were estimated to have a higher subtyping ability, and may be more useful as the supplementary protocols for paratyphoidal fever surveillance, more accurate outbreak case definition, and source tracing.

The preparation of plugs, cell lyses, and plug washes may influence the discriminatory ability of the PFGE (Ribot et al., 2001; Xu et al., 2009). Nevertheless, the enzymes used and the electrophoresis parameters are the most important factors (Goering, 2010). An appropriate enzyme for PFGE analysis should digest the chromosomal DNA into an appropriate number of bands to provide sufficient epidemiological discriminatory ability. In this study, SpeI, XbaI, XhoI, and BlnI all provided optimum numbers of bands. In the standardized PFGE protocol for the subtyping of Salmonella serotypes, XbaI was used as the primary enzyme, followed by BlnI and SpeI, which can be used for the strains that are indistinguishable and need to be confirmed using a second digestion.

In our study, we found that SpeI with specific electrophoresis parameters enables DNA fragments smaller than 310.1 kb to be distinguished, and has higher discrimination ability than XbaI and XhoI. Most of the band sizes yielded by SpeI digestion were smaller than 330 kb. However, the electrophoresis pulse time for Salmonella serotypes (2.2–63.8 s) was optimized for the separation of bands between 30 and 700 kb. Most of the bands yielded by the PulseNet protocol for Salmonella serotypes accumulated, and the patterns were difficult to interpret when SpeI was used. However, the bands yielded with SpeI digestion using the optimal electrophoresis parameters determined in this study distributed evenly. The numbers of patterns and the D values were almost the same for XbaI and XhoI. However, XhoI yielded too many bands, which makes the gels more difficult to interpret. Moreover, some XhoI bands overlapped with each other, which can influence the diversity of the patterns. Therefore, XbaI is the second choice, followed by XhoI. BlnI yielded the fewest bands and is not suitable for Salmonella Paratyphi A subtyping.

Considering the complexity and time-consumption of serotyping of Salmonella isolates, most PulseNet laboratories perform PFGE at the same time as serotyping, to reduce the delay in detection of PFGE pattern clusters and outbreaks. To the outbreak investigation and response, this strategy is valuable and important for PulseNet laboratories. Practically, we think after Salmonella Paratyphi A is identified, the protocols optimized in this study may be used as the supplementary analysis when more subtyping information is needed in the epidemiological investigation, such as the difficultly interpretative inconsistency between the primary PFGE result and epidemiological information and more accurate case definition. In addition, the optimized protocols will be more useful in the clonal structure analysis of the Salmonella Paratyphi A strains collected from different regions and years.

With the optimized protocols, we conducted a retrospective analysis using the strains isolated from different years and provinces after 1995 in China. This analysis also showed that SpeI had a higher discriminatory ability than XbaI. The predominant XbaI pattern, JKPX01.CN0002, was subtyped into nine SpeI patterns, whereas the predominant SpeI pattern, JKPS18.CN0002, was subtyped into six XbaI patterns. The strains from Zhejiang and Guizhou provinces isolated in different years had the same XbaI pattern, but had different SpeI digestion patterns. It was previously demonstrated that better resolution would be provided using a combination of two enzymes in PFGE (Woo, 2005). The combination of XbaI and SpeI in our study also yielded more patterns, which meant a combination of enzymes could be useful when strains could not be distinguished with one enzyme. This could provide more reliable information in determining the extent of the outbreak and the source from the dispersed cases in a paratyphoid fever endemic area.

In our retrospective analysis of Salmonella Paratyphi A strains isolated in China, even though XbaI and SpeI was combined, some of the strains isolated from different provinces and different years were not discriminated, suggesting that those strains were of a conservative clone which caused paratyphoidal fever in China. Our MLST analysis (Han et al., 2010) also showed that a highly conserved clone of Salmonella Paratyphi A caused epidemics in China. Minor variations might accumulate gradually in such a clone during its epidemic progression. Whole genome sequencing of Salmonella Paratyphi A strains is needed to reveal the genomic variations, which will be more valuable to guide the more effective PFGE protocols and even new molecular subtyping protocols such as single nucleotide polymorphism- based assay.

Conclusion

In this study, we compared different endonucleases and electrophoresis parameters for their discriminatory ability in the subtyping of Salmonella Paratyphi A isolates. Based on the distinguishing symptoms of typhoid fever and the longer preclinical period than the diarrhea caused by non-typhoidal Salmonella, the optimized PFGE protocols for Salmonella Paratyphi A subtyping should be useful in outbreak investigations as the complementary protocols of subtyping, except for the standardized protocols for Salmonella in PulseNet, to define the cases more accurately.

Footnotes

Acknowledgments

This study was supported by the Ministry of Health and the Ministry of Science and Technology (grants 2008ZX10004-008 and 2008ZX10004-013).

Disclosure Statement

No competing financial interests exist.

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