• We are sorry, but NCBI web applications do not support your browser and may not function properly. More information
Logo of aemPermissionsJournals.ASM.orgJournalAEM ArticleJournal InfoAuthorsReviewers
Appl Environ Microbiol. Nov 2011; 77(22): 7877–7885.
PMCID: PMC3209009

Methodologies for Salmonella enterica subsp. enterica Subtyping: Gold Standards and Alternatives[down-pointing small open triangle]

Abstract

For more than 80 years, subtyping of Salmonella enterica has been routinely performed by serotyping, a method in which surface antigens are identified based on agglutination reactions with specific antibodies. The serotyping scheme, which is continuously updated as new serovars are discovered, has generated over time a data set of the utmost significance, allowing long-term epidemiological surveillance of Salmonella in the food chain and in public health control. Conceptually, serotyping provides no information regarding the phyletic relationships inside the different Salmonella enterica subspecies. In epidemiological investigations, identification and tracking of salmonellosis outbreaks require the use of methods that can fingerprint the causative strains at a taxonomic level far more specific than the one achieved by serotyping. During the last 2 decades, alternative methods that could successfully identify the serovar of a given strain by probing its DNA have emerged, and molecular biology-based methods have been made available to address phylogeny and fingerprinting issues. At the same time, accredited diagnostics have become increasingly generalized, imposing stringent methodological requirements in terms of traceability and measurability. In these new contexts, the hand-crafted character of classical serotyping is being challenged, although it is widely accepted that classification into serovars should be maintained. This review summarizes and discusses modern typing methods, with a particular focus on those having potential as alternatives for classical serotyping or for subtyping Salmonella strains at a deeper level.

INTRODUCTION

Human salmonellosis is one of the most frequently occurring food-borne diseases worldwide (7, 8, 75). Foods prepared with contaminated raw eggs, egg products, and insufficiently heated poultry meat and pork have been identified as the primary sources of human Salmonella infections (5, 17). Nontyphoid Salmonella strains commonly cause self-limiting gastroenteritis, but severe infections, including bacteremia and meningitis, have also been reported (79). Surveillance programs that detect Salmonella contaminations in a timely manner in the entire food chain (animal feed, living animals, slaughterhouses, retail sector, and restaurants) together with sanitary measures are essential for detecting and preventing human Salmonella infections (14). Therefore, development of rapid and sensitive methods for the detection and characterization of Salmonella may have a significant impact on the disease burden caused by this pathogen.

Classically, Salmonella enterica isolates are identified and typed by phenotypic methods such as biochemical profiling, serotyping and phage typing. Serotyping is an 80-year old method which serves as the basis for the present classification of Salmonella enterica subsp. enterica subtypes (6). Serotyping deciphers the antigenic makeup of the organism by identifying the somatic (O) and flagellar (H) antigens through reactions with specific antisera. Its usefulness in surveillance programs has long been recognized, in spite of the fact that it does not have the capacity to fingerprint strains in a sensitive manner (34). For the latter purpose, pulsed-field gel electrophoresis (PFGE), which was adapted to Salmonella in the 1990s, demonstrated the capacity to identify strains at the origin of an outbreak and rapidly became very popular, to the point where it is considered the gold standard for Salmonella molecular subtyping. During the last 2 decades, surveillance techniques have become easier following the development of alternative methods, most of them DNA based. These new methods improved the performance of the historical methods by displaying higher subtyping sensitivity or facilitated the analysis by requiring no specific technical expertise and by making use of common laboratory reagents (29). Although many methods have been tried with Salmonella, none has emerged clearly as the ideal method. Such a method—if it turns out to exist—should be rapid, robust, portable, and sensitive, producing objective results, differentiating epidemiologically unrelated strains from each other, and grouping all isolates associated with the same source while staying as close as possible to the present classification of Salmonella into subspecies and serovars. The implementation of this ideal method has to be balanced against the budget constraints invariably associated with a technology that needs to be conducted on a massive scale in the routine laboratory.

We provide herein an overview of the methods that are currently available for subtyping Salmonella enterica strains, with an assessment of their respective performance, advantages, and drawbacks. Among the many available methods, which have been reviewed elsewhere (27, 29), we particularly focused on recent typing methods displaying sensitivity below the subspecies level and developed (or being developed) as alternatives to conventional serotyping and PFGE, which are widely considered the gold standards for subtyping Salmonella strains.

TYPING OF SALMONELLA BY PHENOTYPIC METHODS

(i) Serotyping by slide agglutination (Kauffmann-White-Le Minor scheme).

Salmonella serotyping is based on the Kauffmann-White-Le Minor (KW) scheme which is a modification of the original scheme from the 1930s (6, 31, 32). Serotyping is based on the agglutination of bacteria with specific sera to identify variants of the somatic (O) and flagellar (H) antigens. These antigens are highly variable, with 64 O and 114 H variants identified (31, 54). The O antigen is the saccharidic component of the lipopolysaccharide (LPS) exposed on the bacterial surface (70, 77). Its reactivity toward specific antisera forms the basis of the Salmonella serotyping scheme (31). Several O antigens may be expressed together at the surface of a single cell. In contrast, although most salmonellae possess two different copies of the gene encoding the flagellar protein, these bacteria have the unique property of expressing only one flagellar protein at a time (54). Most isolates are therefore termed diphasic (phase I and phase II, also called H1 and H2) with respect to the flagellar antigens. Monophasic Salmonella are not rare; triphasic and quadriphasic subtypes are exceptional (18). Although only one H antigen is expressed at a time, both H1 and H2 can usually be detected in pure cultures because the two phases are expressed by discrete bacterial populations in the same culture or colony. However, if one H phase is undetectable, a method called “phase inversion” is used, which consists of inhibiting the dominant phase by a specific antiserum on a special medium (e.g., Sven Gard) which will favor the growth of the bacterial population expressing the other H antigen (31). By convention, the antigens identified in a given strain are reported in a so-called antigenic formula in which the subspecies number followed by the O, H1, and H2 antigens separated by colons is reported (e.g., I 6,7,14:r:1,2). Historically, serovar names were attributed to groups of Salmonella isolates displaying a common unique antigenic formula. It was noticed later on that some strains had the same antigenic formula but differed in their biochemical profiles. The latter were associated with different subspecies names (S. enterica subsp. salamae = subsp. II; subsp. arizonae = subsp. IIIa; subsp. diarizonae = subsp. IIIb; subsp. houtenae = subsp. IV; subsp. bongori = subsp. V; subsp. indica = subsp. VI). Serotyping thus defines subtypes (i.e., serovars or serotypes) within a subspecies. In this review, typing of strains belonging only to Salmonella enterica subsp. enterica (= subsp. I) is considered, acknowledging that more than 1,500 different serovars are described just for this particular subspecies (31). The slide agglutination test is an early typing technique reflecting the technology available at the time. It is exclusively based on phenotypic characteristics. False-positive reactions may occur as a result of weak, nonspecific agglutination (78). Autoagglutination and loss of antigen expression, such as that observed with rough, nonmotile, and mucoid strains, may occasionally lead to strain untypeability, but these strains typically have little epidemiological significance. The method is intended neither to provide a sensitive fingerprint (e.g., for tracing during an outbreak) nor to define phyletic relationships. It requires the use of over 150 specific antisera and carefully trained personnel (Table 1). It is still defined as the reference method and is commonly used as an initial screening, followed by molecular subtyping to identify outbreak-related strains.

Table 1.
Comparison of the key attributes of some Salmonella typing methods

(ii) Serotyping by antibody microarrays.

Development of a serotyping assay based on SuperEpoxy microarray slides spotted with antibodies and fitting the KW scheme was developed by Cai et al. (19). Identification of 20 commonly isolated and clinically important serovars, representing 80 to 90% of the total Salmonella isolates collected in Canada, was shown to be successful. In this assay, the antibody-antigen reactions are conducted on a microvolume scale on slides following fluorescent labeling of the investigated Salmonella strain. Detection is carried out with a common fluorescence scanner. The main advantages of antibody microarray-based serotyping over traditional serotyping are reduced analysis time, standardized agglutination detection, and simultaneous detection of the O and H antigens, for which the phase inversion step can be skipped thanks to the high sensitivity of detection. Further development of this promising assay is of course conditional upon its successful validation on a much larger number of serovars.

(iii) Other phenotyping methods.

Phage typing is used to discriminate between Salmonella strains belonging to the same serovar. Phage types are assigned on the basis of the ability of a given phage to lyse the investigated strain (3). Initially designed for Salmonella serovar Typhi, Salmonella serovar Paratyphi A, and Salmonella serovar Typhimurium, which are known to be rather monophyletic, the system was later extended to Salmonella serovar Enteritidis (87) and a few other serovars (37). The advantage of phage typing resides in the simplicity of its implementation, which requires only basic laboratory equipment. Ambiguous lysis reactions are common drawbacks, though, and careful coordination between reference laboratories is required in order to ensure reproducibility of the assay (10). The method is also limited by the number of available phages.

MOLECULAR TYPING TECHNIQUES

(i) PFGE.

Pulsed-field gel electrophoresis (PFGE) is a molecular typing method that was adapted to Salmonella in the 1990s (30, 60, 64, 89). The technique is useful for fingerprinting strains in outbreak situations and is relatively inexpensive to perform. Numerous reports have documented the highly discriminatory nature of PFGE in successfully tracking the source of Salmonella infections for different serovars (15, 22, 80, 83). However, PFGE is time-consuming and labor-intensive and does not display equal sensitivity with different serovars (43). Additionally, rigorous standardization of the protocols is necessary to ensure analysis reproducibility. Interlaboratory comparison of the PFGE patterns has been facilitated by the setup of the PulseNet network (http://www.cdc.gov/pulsenet). This network, coordinated by the Centre for Disease Control and Prevention (CDC), is based on a standardized protocol and allows comparison of the PFGE pattern of a given isolate through a set of databases made up of PFGE patterns collected in a country or region. The analysis is frequently described as becoming increasingly unreliable and subjective because of the large number of profile clusters characterized by minor differences only. Nevertheless, since PFGE was historically one of the earliest DNA subtyping systems displaying the capacity to fingerprint Salmonella isolates at a level suitable for outbreak investigation, it rapidly became popular and is considered the gold standard for Salmonella molecular typing.

(ii) Molecular serotyping based on LPS and flagellar structural genes.

To overcome the hand-crafted nature of classical serotyping and the high level technical expertise it requires, alternative methods for the identification of serovars, such as DNA-based serotyping, or “molecular serotyping,” have been developed. For about 10 years, such systems, which are aimed at identifying Salmonella enterica on the basis of the genes coding for the somatic O and H antigens, have been under development. The setup of molecular serotyping systems turned out to be arduous. It supposes that genetic signatures have been identified for each of the existing antigenic types, allowing the corresponding serovar assignment. Three multiplex PCRs which, when combined, could distinguish the most common first- and second-phase H antigens and serogroups based on the length of the amplified DNA fragments were developed by the team of Echeita (23, 35, 36). These combined tests were able to completely serotype 84.6% of 500 routine isolates, while 15.4% yielded ambiguous or incomplete formulas (36). A similar yet more in-depth work was initiated by P. Fields' group at the CDC by systematic sequencing of various alleles of the flagellin genes. The authors could identify 67 of the 114 known flagellar antigenic types and could infer genetic signatures for most of them (56). At the same institution, Fitzgerald et al. later developed a related strategy for serogroup identification based on the O-antigen-encoding biosynthetic rfb genes, from which signature probes were derived and integrated into a suspension bead (Luminex Technology) fluorescence assay (26). A DNA microarray slide combining the serogroup-typing probes and an early version of the flagellar-gene-typing system that could identify the 5 most commonly isolated serovars within Canada was evaluated at about the same time (92). An updated version of the flagellin DNA signatures was recently adapted to a suspension bead assay and proved relatively successful, as it matched traditional results completely for 80.4% of the strains tested in a heterogeneous panel of 500 and yielded partial serotyping results for another 9.2% (57). A combined version associating both serogroup-specific and updated flagellin signatures is currently being evaluated (P. Fields et al., presented at the 13th International Symposium on Salmonella and Salmonellosis, Saint-Malo, France, 2010).

The strength of molecular serotyping methods like those presented above is that they allow better laboratory-to-laboratory reproducibility, require little technical expertise, and deliver results more rapidly. Another advantage resides in the unconditional applicability of the method irrespective of the autoagglutination character or lack of antigen expression of the investigated strains. From an epidemiological perspective, molecular serotyping schemes that fit the KW scheme would allow the continuation of historical surveillance data analysis. Thus, the information collected over many decades can be maintained and updated.

Molecular serotyping has two drawbacks, though; (i) it gives only partial (serogroup) results for strains expressing H antigens with, so far, no identified genetic signature, and (ii) it gives wrong results for some serovars characterized by complex H antigens whose genetic signatures probed by the assay are allelically diverse and therefore not always captured on the array. The method also detects unexpressed flagellin genes found in the genomes of some monophasic variants and nonmotile strains (e.g., Paratyphi A). The problem of allelic diversity and missing H antigen markers at the DNA level can theoretically be solved if the nucleotide sequences of all the existing H antigen markers and alleles are identified and used to derive capture probes or probe sets. In contrast, phenotypic characteristics such as flagellin surface exposure or strain motility can hardly be probed by DNA hybridization, as it requires functionality of the numerous components involved in flagellar expression and assembly. It should be noticed, however, that detection of unexpressed flagellar genes is usually not an issue in serovar inference made by molecular serotyping. Future versions may include probes targeting genes with no O- or H-antigen biosynthetic function to improve the distinction between closely related serovars (57).

Thus, although technically simpler and amenable to a highly successful level of coverage in future versions, molecular serotyping methods based on LPS and flagellar genes will probably never mirror exactly and completely the classical serotyping results due to intrinsic differences in their respective concepts (probing of genes instead of assembled antigens). In addition, like classical serotyping, molecular serotyping is not appropriate for strain fingerprinting in outbreak situations (Table 1).

(iii) Molecular serotyping based on genomic markers.

It has been noticed in several independent studies that global genome diversity and surface antigen variability evolved in parallel within Salmonella subspecies (55, 81). Therefore, a number of molecular methods based on markers unrelated to the genetic determinants of the O and H antigens have been proposed to infer the serovar of Salmonella strains. A molecular serotyping system based on the multiplexed ligase chain reaction (LCR) assay, analyzed on a low-density DNA microarray platform, has been made commercially available as PremiTest Salmonella by Check-Points (Wageningen, The Netherlands) (4, 88). The system makes use of genetic markers selected to yield unique microarray hybridization profiles, enabling identification at both the genus and serovar levels of the most commonly encountered Salmonella enterica subsp. enterica serovars. When assessed in our reference laboratory on 754 strains of animal origin sent for routine typing, the system performed almost as well as the slide agglutination method. Some drawbacks were observed for uncommon serovars, though, which were either misidentified by the system (0.6%), identified as “unknown” (2.5%), or undistinguishable from other uncommon serovars (2.1%) (88). The latest version of PremiTest Salmonella (v7.1) screens 27 genetic markers and has the capability of recognizing >100 different serovars (A. Brisabois et al., presented at the 13th International Symposium on Salmonella and Salmonellosis, Saint-Malo, France, 2010; P. Vos and J. Thijssen, personal communication), making it the most advanced molecular serotyping method currently available commercially. The genetic markers screened in this assay were, however, not divulged by the manufacturer, rendering its evaluation difficult from a conceptual point of view. The sensitivity of the PremiTest goes somewhat farther than the serovar level, especially for polyphyletic strains, but is not sufficient for strain fingerprinting in outbreak situations. Moreover, its cost may preclude systematic use in routine analysis.

Another molecular serotyping method was developed by Kim et al. (45). This method is based on the PCR amplification of 12 genetic loci present in specific serovars and absent in others. The genomic regions chosen for this serotyping study are derived from whole-genome sequence comparisons reported earlier (25, 65, 67, 68). The method allows the identification of the 28 most common clinically relevant S. enterica subsp. enterica serovars encountered in the United States and was reported to be nearly as discriminatory as conventional serotyping. Ninety-seven percent (98/111) of clinical isolates representing the 30 most common U.S. serovars were correctly identified using the above-described assay in a blind screening test (45). It requires, however, that several PCRs be conducted and analyzed by gel electrophoresis separately for each strain investigated.

High-throughput methods were later developed from the above-described one. First, a 16-plex PCR assay based on the same markers plus an additional set of four that could identify the most common serovars of S. enterica in the United States was described (47). Amplification is conducted in a single 16-plex assay monitored by capillary electrophoresis, substantially improving the associated laboratory work. Among the four added markers is the phase II flagellin gene (fljB) used to distinguish Salmonella serovar Typhimurium from its supposed monophasic variant, Salmonella serovar 4,[5],12:i:−. When tested on a collection of 751 isolates representing 50 serovars, the assay exactly matched classical serotyping results in 66% of cases (32 serovars) while yielding ambiguous results in other cases. Further incorporation of new target sequences is currently under development and is expected to increase the specificity of the assay (47).

A so-called “PCR on a chip” assay derived from the method of Kim et al. (45) was recently developed in which PCR products are amplified in situ and detected with a universal fluorescent hybridization probe (58). The main advantages of this method are the nanoliter format and the high-throughput processing. The serovar coverage of the latter assay is identical to that of the original system of Kim et al. and hence could be improved by merging additional primer pairs.

A third extended version of the original multiplex assays was obtained by adding three virulence genes, enabling the detection of 12 additional serovars (total of 42 serovars) (66). In the same study, a 37-spot DNA microarray made of 70-mer oligonucleotides derived from previous work (45, 67) was evaluated in parallel and reported to perform well in assessing 56 common clinical isolates belonging to 29 serovars. Many serovars and strains should be tested, however, to gain a better picture of this microarray's performance.

The finding of two clustered regularly interspaced palindromic repeat (CRISPR) loci in the Salmonella genome was used by F. X. Weill and coworkers to build a database containing sequence signatures for a number of Salmonella serovars (90). Identification and database comparison of the nucleotide sequences of the variable portion of the CRISPR loci, which is determined either by DNA sequencing or by hybridization in a liquid bead microarray suspension assay, allows indirect serovar identification. The method is basically identical to the popular spoligotyping method designed for Mycobacterium subtyping (41). It has been assessed on 120 different Salmonella serovars so far and is reported to be sensitive below the serovar level, particularly for polyphyletic serovars such as Dublin, Paratyphi B, and Infantis (L. Fabre et al., presented at the 13th International Symposium on Salmonella and Salmonellosis, Saint-Malo, France, 2010). The system looks promising and awaits an independent evaluation by reference laboratories.

(iv) Molecular subtyping by whole-genome (ORFeome) comparisons.

Typing methodologies derived from comparative genomics of S. enterica subsp. enterica offered the possibility of deeply investigating the genetic content of Salmonella strains. Using microarrays representing almost all annotated ORFs from both Salmonella serovar Typhimurium LT2 and Salmonella serovar Typhi CT18 strains, the entire genome content of recent clinical isolates of the most prevalent S. enterica serovars in the U.S. was characterized (67). During this study, it was noticed that gene contents sometimes differed more within a serovar than between serovars, as the probable result of gene exchange events occurring in the loci defining a serovar. Multiplex PCR and real-time assays derived from the above study were later developed (9). Such methods are promising in terms of global sensitivity and offer the possibility of accurately evaluating the genetic relatedness of the investigated strains. These methods await further validation with additional ORFs and testing on a large panel of serovars and strains.

Thus, as noticed for methods based on LPS and flagellar genes, molecular serotyping based on genomic markers does not exactly mirror classical serotyping. Currently, these methods are unable to identify all existing serovars. Some have the potential to reach a sensitivity level that is satisfactory for screening or provisional identification when the use of reference methods is either not required or not applicable (autoagglutinable strains or strains defective in antigen expression). They have some advantages in terms of cost, rapidity, and throughput (Table 1). Microarray-based systems are still expensive but could soon become affordable given their popularity and constant development. The open format of many of these array systems allows new markers to be incorporated in upcoming versions without affecting the parameters of the whole system, the latter being the hallmark of multiplex PCR methods. In contrast, microarrays that probe the entire Salmonella genome require genomic DNA purification, processing, and labeling, which are expensive, difficult-to-automate steps not suited for high-throughput processing. A technical challenge remains when sensitivity at the nucleotide level (possibly the single-nucleotide level) is required in the analysis of the probed DNA fragments. Some other methods, like multilocus sequence typing and single-nucleotide polymorphism typing, which were first developed to discriminate beyond the serovar level, have also shown usefulness in serovar identification. These methods are discussed below.

(v) MLST.

A first multilocus sequence typing (MLST) scheme based on fragments from 7 housekeeping genes was developed in 2002 to study the clonality of Salmonella serovar Typhi and its divergence from the other S. enterica subspecies, which was estimated to have occurred some 50,000 years ago (44). These housekeeping genes (aroC, dnaN, hemD, hisD, purE, sucA, and thrA) were selected from the genome of Salmonella serovar Typhi CT18 (65) based on (i) their scattered positions on the chromosome, (ii) the presence of genes with known functions in the surrounding DNA, and (iii) the lack of any diversifying selection pressure (44). This MLST scheme could identify no more than 3 sequence types (STs) within a huge collection of Salmonella serovar Typhi strains from various origins, while S. enterica strains belonging to other serovars clustered totally apart. Thus, the method looked promising mostly for typing nontyphoidal Salmonella strains and later became very popular. The sequencing data were collected and made available online on the S. enterica MLST database website hosted at the University College of Cork, Ireland (http://mlst.ucc.ie/mlst/dbs/Senterica).

A second MLST scheme based on 4 polymorphic genes (16S RNA, pduF, glnA, and manB) turned to be efficient in discriminating serovars (46). The developers of this scheme also reported discrimination potential within serovars and between strains of either environmental or clinical origin (46). A variant of this MLST scheme assessing spaM (a virulence gene) instead of the 16S RNA gene showed no genetic diversity among Salmonella serovar Typhimurium strains isolated from cattle in the U.S. (24). Foley et al. (28) showed that the latter MLST displayed insufficient diversity within Salmonella serovar Typhimurium unless fimbrial (pefB and fimH) and virulence (hilA) genes were added to the system, thereby increasing the discriminatory potential up to the level of PFGE.

Another MLST study aimed at globally discriminating S. enterica belonging to 11 serovars commonly encountered in the U.S. was published 3 years later (81). The method also proved efficient for differentiating below the serovar level, especially when polyphyletic serovars were being assessed. This MLST scheme was initially based on seven housekeeping and virulence genes and later reduced to a three-gene sequence typing scheme consisting of the most variable genes of the initial set (manB, fimA, and mdh) (2).

An MLST scheme combining two housekeeping genes with the two flagellin genes (fliC and fljB) was developed by Tankouo-Sandjong et al. (82). This combination aimed at establishing a uniform sensitivity threshold applicable at both the inter- and intraserovar levels. The method showed better discriminatory ability (one ST for 1.23 isolates) than the MLST methods of Sukhnanand et al. (81) (one ST for 2.64 isolates) and Kidgell et al. (44) (one ST for 2.2 isolates).

Ross et al. (72) developed a conceptually different MLST scheme targeting prophage loci. The comparative analysis of 73 Salmonella serovar Typhimurium strains showed that this MLST was more discriminative than PFGE or MLSTs based on housekeeping genes.

Recently, Liu et al. (50) developed a MLST scheme based exclusively on virulence genes (sseL and fimH) and on the two CRISPR loci described above. This MLST scheme provided better discrimination of Salmonella serovar Enteritidis strains than PFGE and accurately differentiated outbreak strains and clones of the nine Salmonella serovars most commonly associated with human disease.

In summary, the MLST scheme of Kidgell et al. (44) remains the most popular thanks to the support brought by the online public S. enterica MLST database, although it is clear that other schemes have proven more sensitive and can compete with PFGE for the discrimination of closely related strains. The drawbacks of MLST are the substantial cost and laboratory work required to amplify, determine, and proofread the nucleotide sequence of the target DNA fragments, making the method hardly suitable for routine laboratory testing.

(vi) SNP discovery and typing.

The discovery of SNPs has been facilitated by the genome sequencing of several strains belonging to either different or identical serovars. Much effort has been focused on Salmonella serovar Typhi for obvious public health reasons. Given the highly monomorphic character of this human-adapted serovar, clonal fingerprinting of Salmonella serovar Typhi strains requires that single-nucleotide variants be discovered and sensitive techniques used for their discrimination. Such sequence polymorphisms were identified by nucleotide sequence comparison of Salmonella serovar Typhi strains (39, 62) or by denaturing high-performance liquid chromatography (dHPLC) (74).

Methods that can identify critical nucleotides in a subset of polymorphic markers, sometimes in a highly multiplexed manner, have arisen. Ben-Darif et al. (11) developed a multiplex primer extension (MPE) assay to genotype multiple known SNPs selected from the MLST scheme of Kidgell et al. (44). The 15 selected SNPs could successfully differentiate the five most prevalent S. enterica serovars in the United Kingdom.

High-density array platforms assessing 1,500 SNPs were used in two studies to type Salmonella serovar Typhi isolates at an unprecedented level of sensitivity (38, 42). A simpler and cost-effective SNP typing method was developed by Octavia and Lan (63). This method assesses each SNP individually using hairpin-shaped primers (33) formatted to preferentially amplify the actual nucleotide found at a given SNP position. Bishop et al. (C. Bishop, T. Dalmann, and J. Wain, presented at the 13th International Symposium on Salmonella and Salmonellosis, Saint-Malo, France, 2010) are designing a method to detect SNPs in Salmonella Paratyphi A based on single-base extension of DNA probes combined in four multiplex PCR assays. The originality resides in the analysis of the 47 generated amplicons, which are passed through a mass spectrometer. Finally, a low-density microarray assessing 62 markers directly amplified from purified genomic DNA by ligation detection reaction was recently developed with the aim of identifying virulence-associated gene repertoires within common serovars (1).

In summary, typing methods targeting a few informative SNPs and requiring little or no specific instrumentation represent a cost-effective alternative to sequence-based typing methods like full MLST characterization or, at the farthest extreme, full genome sequencing. The distinct advantage of SNP- and other nucleotide sequence-based methods over profile-generating methods is that genetic relationships can be established on the basis of discrete data that are directly suitable for biocomputing and statistical analysis. As described above, SNP targets can be identified either in silico (full-genome comparisons, screening of MLST databases) or experimentally (dHPLC). The sensitivity of typing methods targeting just a few SNPs is limited either by the maximum number of loci that can be assessed in a single-tube test according to the method being used or by the analysis platform or both. The highly multiplexed capability of some SNP-typing array platforms allowed in-depth genetic assessment of Salmonella serovar Typhi strains for the first time. The potential application of some of the numerous (>1,500) SNP markers displaying variability in Salmonella serovar Typhi for the subtyping of strains belonging to other—possibly any—S. enterica serovars, such as that demonstrated earlier with an MLST scheme (44), remains an interesting challenge.

(vii) MLVA.

Several multiple-locus variable-number tandem repeat analysis (MLVA) protocols for subtyping Salmonella serovar Typhimurium (20, 48, 49, 73, 91), Enteritidis (12, 16, 53, 73), Typhi (51, 61, 69), Infantis (71), Newport (21, 91), Paratyphi A (84), Saintpaul (59), and Gallinarum (13) isolates have been published during the last decade. The method has proven very useful for detecting and investigating outbreaks, since it has the capacity to differentiate closely related strains (16, 85). It is technically simple and inexpensive to perform. However, the scope of each MLVA is commonly restricted to a unique serovar, making MLVA a second-line typing method with no usefulness for serovar assignment or for global phylogenetic studies. A drawback of MLVA commonly observed during assessing of small tandem repeat motifs is genetic homoplasy, leading to apparent relatedness of the investigated strains (86).

(viii) Molecular typing with composite microarrays.

Many different microarray setups were used to screen the genome of Salmonella. Some of these are described above. Malorny et al. (52) developed a composite microarray for the simultaneous molecular characterization and typing of Salmonella enterica subsp. enterica isolates. This microarray contains 109 35- to 40-mer oligonucleotide probes detecting flagellar and somatic antigen-encoding genes (serogroup or serovar specific), virulence genes located within or outside the pathogenicity islands, phage-associated genes, and antibiotic resistance determinants. It was used to study the epidemiology of Salmonella strains and showed good agreement with gene-specific PCRs and phenotypic methods. Huehn and Malorny (40) later improved the sensitivity of the above-described microarray by immobilizing 282 60-mer probes targeting genes associated with pathogenicity, antibiotic resistance, fimbriae, prophages, flagella, LPS, plasmids, insertion sequence elements, and metabolism.

Scaria et al. (76) developed a similar but larger microarray in order to subtype the 14 most common disease-causing Salmonella serovars in the United States. This microarray consists of 414 immobilized 70-mer oligonucleotides targeting both virulence and housekeeping genes of S. enterica subspecies I, such as fimbrial genes, pathogenicity islands, prophage elements, and serovar-specific genes. The system displays typing capacity, allowing inter- and intraserovar phylogenetic relationships to be explored with high sensitivity. This microarray could probably be extended to more Salmonella serovars, which would require validation on a much larger scale.

The scope of composite microarrays is thus to provide in a single assay multiple data on a given strain, such as serovar assignment, virulence profile, antibiotic-resistance profile, and a genetic fingerprint useful for outbreak investigations. The popularity of microarray analyses led to a substantial decrease in their cost, and so cost may no longer preclude their use in the routine laboratory.

CONCLUSION AND PERSPECTIVES

Many methods have been and are still being developed for the subtyping of Salmonella. Each of them has its own advantages and drawbacks in terms of cost, speed, robustness, and sensitivity (Table 1). Molecular methods developed as alternatives to classical serotyping have generally proven very successful, even if they do not deliver results that exactly and completely mirror those obtained by the current reference method, which probes surface antigens with antisera. The observed discrepancies result from the intrinsic nature of molecular versus phenotypic methods, which cannot be perfectly correlated due to the multiple differences that characterize genes on the one hand and antigens exposed at the bacterial surface on the other. These minor differences certainly do not affect the usefulness of the alternative molecular methods. However, it may preclude their use in contexts where strict observation of the reference methodology and classification rules are imposed. Whenever it has been assessed by classical or modern methodologies, the historical classification into serovars has been shown to be useful, and it is generally accepted that this classification should be maintained.

Molecular subtyping methods have proven highly valuable in characterizing and differentiating Salmonella strains at a sensitive level for epidemiological studies. Housekeeping genes, virulence determinants, antibiotic resistance markers, mobile genetic elements, prophage genomes, and sequence repeats have all been used as targets, either alone or combined. To evaluate the level of sensitivity reached by these new methods, PFGE is often used as the reference method. For many of them, this level relies on the number of markers included in the assay and on the capacity of the chosen platform to analyze them in a single run. In this respect, microarrays achieved a significant breakthrough by allowing dozens of such markers to be analyzed at once. Methodological challenges remain for multiple SNP amplification and typing. In addition, high costs often preclude the use of many such methods for routine use. However, as costs fall and automation improves, global effectiveness and speed may soon favor a more systematic use of these new DNA-based assays.

ACKNOWLEDGMENTS

We thank J. Godfroid and H. Imberechts for carefully proofreading the manuscript.

Footnotes

[down-pointing small open triangle]Published ahead of print on 19 August 2011.

REFERENCES

1. Aarts H. J., et al. 2011. A multiplex ligation detection assay for the characterization of Salmonella enterica strains. Int. J. Food Microbiol. 145(Suppl. 1):S68–S78 [PubMed]
2. Alcaine S. D., et al. 2006. Multilocus sequence typing supports the hypothesis that cow- and human-associated Salmonella isolates represent distinct and overlapping populations. Appl. Environ. Microbiol. 72:7575–7585 [PMC free article] [PubMed]
3. Anderson E. S., Williams R. E. 1956. Bacteriophage typing of enteric pathogens and staphylococci and its use in epidemiology. J. Clin. Pathol. 9:94–127 [PMC free article] [PubMed]
4. Andreoli P., Thijssen J., Anthony R., Vos P., De Levita W. April 2004. Fast method for detecting micro-organisms in food samples. International patent WO 2004/106547 A2
5. Anonymous 2006. The community summary report on trends and sources of zoonoses, zoonotic agents, antimicrobial resistance and foodborne outbreaks in the European Union in 2005. European Food Safety Authority, Parma, Italy
6. Anonymous 1934. The genus Salmonella Lignieres, 1900. J. Hyg. (Lond.) 34:333–350 [PMC free article] [PubMed]
7. Anonymous 2001. Report to the European Parliament and to the Council on the measures to be put in force for the control and prevention of zoonoses. Commission of the European Communities, Brussels, Belgium
8. Anonymous 2008. Trends and sources: report on zoonotic agents in Belgium in 2006. Federal Agency for the Safety of the Food Chain, Working Group on Foodborne Infections and Intoxications, Brussels, Belgium
9. Arrach N., et al. 2008. Salmonella serovar identification using PCR-based detection of gene presence and absence. J. Clin. Microbiol. 46:2581–2589 [PMC free article] [PubMed]
10. Baggesen D. L., Sorensen G., Nielsen E. M., Wegener H. C. 2010. Phage typing of Salmonella Typhimurium—is it still a useful tool for surveillance and outbreak investigation? Euro Surveill. 15:19471. [PubMed]
11. Ben-Darif E., et al. 2010. Development of a multiplex primer extension assay for rapid detection of Salmonella isolates of diverse serotypes. J. Clin. Microbiol. 48:1055–1060 [PMC free article] [PubMed]
12. Beranek A., et al. 2009. Multiple-locus variable-number tandem repeat analysis for subtyping of Salmonella enterica subsp. enterica serovar Enteritidis. Int. J. Med. Microbiol. 299:43–51 [PubMed]
13. Bergamini F., Iori A., Massi P., Pongolini S. 2011. Multilocus variable-number of tandem-repeats analysis of Salmonella enterica serotype Gallinarum and comparison with pulsed-field gel electrophoresis genotyping. Vet. Microbiol. 149:430–436 [PubMed]
14. Bertrand S., et al. 2010. Lessons learned from the management of a national outbreak of Salmonella Ohio linked to pork meat processing and distribution. J. Food. Prot. 73:529–534 [PubMed]
15. Best E. L., et al. 2009. Drug-resistant Salmonella Typhimurium DT 120: use of PFGE and MLVA in a putative international outbreak investigation. Microb. Drug Resist. 15:133–138 [PubMed]
16. Boxrud D., et al. 2007. Comparison of multiple-locus variable-number tandem repeat analysis, pulsed-field gel electrophoresis, and phage typing for subtype analysis of Salmonella enterica serotype Enteritidis. J. Clin. Microbiol. 45:536–543 [PMC free article] [PubMed]
17. Buchholz U., et al. 2005. An outbreak of Salmonella München in Germany associated with raw pork meat. J. Food Prot. 68:273–276 [PubMed]
18. Burnens A. P., Stanley J., Sechter I., Nicolet J. 1996. Evolutionary origin of a monophasic Salmonella serovar, 9,12:l,v:−, revealed by IS200 profiles and restriction fragment polymorphisms of the fljB gene. J. Clin. Microbiol. 34:1641–1645 [PMC free article] [PubMed]
19. Cai H. Y., Lu L., Muckle C. A., Prescott J. F., Chen S. 2005. Development of a novel protein microarray method for serotyping Salmonella enterica strains. J. Clin. Microbiol. 43:3427–3430 [PMC free article] [PubMed]
20. Chiou C. S., et al. 2010. Development and evaluation of multilocus variable number tandem repeat analysis for fine typing and phylogenetic analysis of Salmonella enterica serovar Typhimurium. Int. J. Food Microbiol. 142:67–73 [PubMed]
21. Davis M. A., et al. 2009. Multilocus variable-number tandem-repeat method for typing Salmonella enterica serovar Newport. J. Clin. Microbiol. 47:1934–1938 [PMC free article] [PubMed]
22. Dionisi A. M., Carattoli A., Luzzi I., Magistrali C., Pezzotti G. 2006. Molecular genotyping of Salmonella enterica Abortusovis by pulsed field gel electrophoresis. Vet. Microbiol. 116:217–223 [PubMed]
23. Echeita M. A., Herrera S., Garaizar J., Usera M. A. 2002. Multiplex PCR-based detection and identification of the most common Salmonella second-phase flagellar antigens. Res. Microbiol. 153:107–113 [PubMed]
24. Fakhr M. K., Nolan L. K., Logue C. M. 2005. Multilocus sequence typing lacks the discriminatory ability of pulsed-field gel electrophoresis for typing Salmonella enterica serovar Typhimurium. J. Clin. Microbiol. 43:2215–2219 [PMC free article] [PubMed]
25. Farrell J. J., et al. 2005. Broad-range (pan) Salmonella and Salmonella serotype Typhi-specific real-time PCR assays: potential tools for the clinical microbiologist. Am. J. Clin. Pathol. 123:339–345 [PubMed]
26. Fitzgerald C., et al. 2007. Multiplex, bead-based suspension array for molecular determination of common Salmonella serogroups. J. Clin. Microbiol. 45:3323–3334 [PMC free article] [PubMed]
27. Foley S. L., Lynne A. M., Nayak R. 2009. Molecular typing methodologies for microbial source tracking and epidemiological investigations of Gram-negative bacterial foodborne pathogens. Infect. Genet. Evol. 9:430–440 [PubMed]
28. Foley S. L., et al. 2006. Comparison of subtyping methods for differentiating Salmonella enterica serovar Typhimurium isolates obtained from food animal sources. J. Clin. Microbiol. 44:3569–3577 [PMC free article] [PubMed]
29. Foley S. L., Zhao S., Walker R. D. 2007. Comparison of molecular typing methods for the differentiation of Salmonella foodborne pathogens. Foodborne Pathog. Dis. 4:253–276 [PubMed]
30. Garaizar J., et al. 2000. Suitability of PCR fingerprinting, infrequent-restriction-site PCR, and pulsed-field gel electrophoresis, combined with computerized gel analysis, in library typing of Salmonella enterica serovar Enteritidis. Appl. Environ. Microbiol. 66:5273–5281 [PMC free article] [PubMed]
31. Grimont P. A. D., Weill F. X. 2007. Antigenic formulae of the Salmonella serovars. Institut Pasteur & WHO Collaborating Centre for Reference and Research on Salmonella, Paris, France
32. Guibourdenche M., et al. 2010. Supplement 2003-2007 (no. 47) to the White-Kauffmann-Le Minor scheme. Res. Microbiol. 161:26–29 [PubMed]
33. Hazbon M. H., Alland D. 2004. Hairpin primers for simplified single-nucleotide polymorphism analysis of Mycobacterium tuberculosis and other organisms. J. Clin. Microbiol. 42:1236–1242 [PMC free article] [PubMed]
34. Herikstad H., Motarjemi Y., Tauxe R. V. 2002. Salmonella surveillance: a global survey of public health serotyping. Epidemiol. Infect. 129:1–8 [PMC free article] [PubMed]
35. Herrera-Leon S., et al. 2004. Multiplex PCR for distinguishing the most common phase-1 flagellar antigens of Salmonella spp. J. Clin. Microbiol. 42:2581–2586 [PMC free article] [PubMed]
36. Herrera-Leon S., et al. 2007. Blind comparison of traditional serotyping with three multiplex PCRs for the identification of Salmonella serotypes. Res. Microbiol. 158:122–127 [PubMed]
37. Hickman-Brenner F. W., Stubbs A. D., Farmer J. J., III 1991. Phage typing of Salmonella Enteritidis in the United States. J. Clin. Microbiol. 29:2817–2823 [PMC free article] [PubMed]
38. Holt K. E., et al. 2010. High-throughput bacterial SNP typing identifies distinct clusters of Salmonella Typhi causing typhoid in Nepalese children. BMC Infect. Dis. 10:144. [PMC free article] [PubMed]
39. Holt K. E., et al. 2008. High-throughput sequencing provides insights into genome variation and evolution in Salmonella Typhi. Nat. Genet. 40:987–993 [PMC free article] [PubMed]
40. Huehn S., Malorny B. 2009. DNA microarray for molecular epidemiology of Salmonella. Methods Mol. Biol. 551:249–285 [PubMed]
41. Kamerbeek J., et al. 1997. Simultaneous detection and strain differentiation of Mycobacterium tuberculosis for diagnosis and epidemiology. J. Clin. Microbiol. 35:907–914 [PMC free article] [PubMed]
42. Kariuki S., et al. 2010. Typhoid in Kenya is associated with a dominant multidrug-resistant Salmonella enterica serovar Typhi haplotype that is also widespread in Southeast Asia. J. Clin. Microbiol. 48:2171–2176 [PMC free article] [PubMed]
43. Kerouanton A., et al. 2007. Pulsed-field gel electrophoresis subtyping database for foodborne Salmonella enterica serotype discrimination. Foodborne Pathog. Dis. 4:293–303 [PubMed]
44. Kidgell C., et al. 2002. Salmonella Typhi, the causative agent of typhoid fever, is approximately 50,000 years old. Infect. Genet. Evol. 2:39–45 [PubMed]
45. Kim S., et al. 2006. Multiplex PCR-based method for identification of common clinical serotypes of Salmonella enterica subsp. enterica. J. Clin. Microbiol. 44:3608–3615 [PMC free article] [PubMed]
46. Kotetishvili M., Stine O. C., Kreger A., Morris J. G., Jr., Sulakvelidze A. 2002. Multilocus sequence typing for characterization of clinical and environmental Salmonella strains. J. Clin. Microbiol. 40:1626–1635 [PMC free article] [PubMed]
47. Leader B. T., Frye J. G., Hu J., Fedorka-Cray P. J., Boyle D. S. 2009. High-throughput molecular determination of Salmonella enterica serovars by use of multiplex PCR and capillary electrophoresis analysis. J. Clin. Microbiol. 47:1290–1299 [PMC free article] [PubMed]
48. Lindstedt B. A., Heir E., Gjernes E., Kapperud G. 2003. DNA fingerprinting of Salmonella enterica subsp. enterica serovar Typhimurium with emphasis on phage type DT104 based on variable number of tandem repeat loci. J. Clin. Microbiol. 41:1469–1479 [PMC free article] [PubMed]
49. Lindstedt B. A., Vardund T., Aas L., Kapperud G. 2004. Multiple-locus variable-number tandem-repeats analysis of Salmonella enterica subsp. enterica serovar Typhimurium using PCR multiplexing and multicolor capillary electrophoresis. J. Microbiol. Methods 59:163–172 [PubMed]
50. Liu F., et al. 2011. Novel virulence gene and CRISPR multilocus sequence typing scheme for subtyping the major serovars of Salmonella enterica subsp. enterica. Appl. Environ. Microbiol. 77:1946–1956 [PMC free article] [PubMed]
51. Liu Y., et al. 2003. Molecular typing of Salmonella enterica serovar Typhi isolates from various countries in Asia by a multiplex PCR assay on variable-number tandem repeats. J. Clin. Microbiol. 41:4388–4394 [PMC free article] [PubMed]
52. Malorny B., Bunge C., Guerra B., Prietz S., Helmuth R. 2007. Molecular characterisation of Salmonella strains by an oligonucleotide multiprobe microarray. Mol. Cell. Probes 21:56–65 [PubMed]
53. Malorny B., Junker E., Helmuth R. 2008. Multi-locus variable-number tandem repeat analysis for outbreak studies of Salmonella enterica serotype Enteritidis. BMC Microbiol. 8:84. [PMC free article] [PubMed]
54. McQuiston J. R., Fields P. I., Tauxe R. V., Logsdon J. M., Jr 2008. Do Salmonella carry spare tyres? Trends Microbiol. 16:142–148 [PubMed]
55. McQuiston J. R., et al. 2008. Molecular phylogeny of the salmonellae: relationships among Salmonella species and subspecies determined from four housekeeping genes and evidence of lateral gene transfer events. J. Bacteriol. 190:7060–7067 [PMC free article] [PubMed]
56. McQuiston J. R., et al. 2004. Sequencing and Comparative analysis of flagellin genes fliC, fljB, and flpA from Salmonella. J. Clin. Microbiol. 42:1923–1932 [PMC free article] [PubMed]
57. McQuiston J. R., Waters R. J., Dinsmore B. A., Mikoleit M. L., Fields P. I. 2011. Molecular determination of H antigens of Salmonella using a microsphere-based liquid array. J. Clin. Microbiol. 49:565–573 [PMC free article] [PubMed]
58. Mertes F., Biens K., Lehrach H., Wagner M., Dahl A. 2010. High-throughput universal probe Salmonella serotyping (UPSS) by nanoPCR. J. Microbiol. Methods 83:217–223 [PubMed]
59. Munnoch S. A., et al. 2009. A multi-state outbreak of Salmonella Saintpaul in Australia associated with cantaloupe consumption. Epidemiol. Infect. 137:367–374 [PubMed]
60. Murase T., Nagato M., Shirota K., Katoh H., Otsuki K. 2004. Pulsed-field gel electrophoresis-based subtyping of DNA degradation-sensitive Salmonella enterica subsp. enterica serovar Livingstone and serovar Cerro isolates obtained from a chicken layer farm. Vet. Microbiol. 99:139–143 [PubMed]
61. Octavia S., Lan R. 2009. Multiple-locus variable-number tandem-repeat analysis of Salmonella enterica serovar Typhi. J. Clin. Microbiol. 47:2369–2376 [PMC free article] [PubMed]
62. Octavia S., Lan R. 2007. Single-nucleotide-polymorphism typing and genetic relationships of Salmonella enterica serovar Typhi isolates. J. Clin. Microbiol. 45:3795–3801 [PMC free article] [PubMed]
63. Octavia S., Lan R. 2010. Single nucleotide polymorphism typing of global Salmonella enterica serovar Typhi isolates by use of a hairpin primer real-time PCR assay. J. Clin. Microbiol. 48:3504–3509 [PMC free article] [PubMed]
64. Olsen J. E., Skov M. N., Threlfall E. J., Brown D. J. 1994. Clonal lines of Salmonella enterica serotype Enteritidis documented by IS200-, ribo-, pulsed-field gel electrophoresis and RFLP typing. J. Med. Microbiol. 40:15–22 [PubMed]
65. Parkhill J., et al. 2001. Complete genome sequence of a multiple drug resistant Salmonella enterica serovar Typhi CT18. Nature 413:848–852 [PubMed]
66. Peterson G., et al. 2010. Development of microarray and multiplex polymerase chain reaction assays for identification of serovars and virulence genes in Salmonella enterica of human or animal origin. J. Vet. Diagn. Invest. 22:559–569 [PubMed]
67. Porwollik S., et al. 2004. Characterization of Salmonella enterica subspecies I genovars by use of microarrays. J. Bacteriol. 186:5883–5898 [PMC free article] [PubMed]
68. Porwollik S., et al. 2005. Differences in gene content between Salmonella enterica serovar Enteritidis isolates and comparison to closely related serovars Gallinarum and Dublin. J. Bacteriol. 187:6545–6555 [PMC free article] [PubMed]
69. Ramisse V., et al. 2004. Variable number of tandem repeats in Salmonella enterica subsp. enterica for typing purposes. J. Clin. Microbiol. 42:5722–5730 [PMC free article] [PubMed]
70. Reeves P. R., et al. 1996. Bacterial polysaccharide synthesis and gene nomenclature. Trends Microbiol. 4:495–503 [PubMed]
71. Ross I. L., Heuzenroeder M. W. 2008. A comparison of three molecular typing methods for the discrimination of Salmonella enterica serovar Infantis. FEMS Immunol. Med. Microbiol. 53:375–384 [PubMed]
72. Ross I. L., Heuzenroeder M. W. 2005. Discrimination within phenotypically closely related definitive types of Salmonella enterica serovar Typhimurium by the multiple amplification of phage locus typing technique. J. Clin. Microbiol. 43:1604–1611 [PMC free article] [PubMed]
73. Ross I. L., Parkinson I. H., Heuzenroeder M. W. 2009. The use of MAPLT and MLVA analyses of phenotypically closely related isolates of Salmonella enterica serovar Typhimurium. Int. J. Med. Microbiol. 299:37–41 [PubMed]
74. Roumagnac P., et al. 2006. Evolutionary history of Salmonella Typhi. Science 314:1301–1304 [PMC free article] [PubMed]
75. Scallan E., et al. 2011. Foodborne illness acquired in the United States—major pathogens. Emerg. Infect. Dis. 17:7–15 [PMC free article] [PubMed]
76. Scaria J., et al. 2008. Microarray for molecular typing of Salmonella enterica serovars. Mol. Cell. Probes 22:238–243 [PMC free article] [PubMed]
77. Schnaitman C. A., Klena J. D. 1993. Genetics of lipopolysaccharide biosynthesis in enteric bacteria. Microbiol. Rev. 57:655–682 [PMC free article] [PubMed]
78. Schrader K. N., Fernandez-Castro A., Cheung W. K., Crandall C. M., Abbott S. L. 2008. Evaluation of commercial antisera for Salmonella serotyping. J. Clin. Microbiol. 46:685–688 [PMC free article] [PubMed]
79. Sirinavin S., Jayanetra P., Thakkinstian A. 1999. Clinical and prognostic categorization of extraintestinal nontyphoidal Salmonella infections in infants and children. Clin. Infect. Dis. 29:1151–1156 [PubMed]
80. Sivapalasingam S., et al. 2003. A multistate outbreak of Salmonella enterica Serotype Newport infection linked to mango consumption: impact of water-dip disinfestation technology. Clin. Infect. Dis. 37:1585–1590 [PubMed]
81. Sukhnanand S., et al. 2005. DNA sequence-based subtyping and evolutionary analysis of selected Salmonella enterica serotypes. J. Clin. Microbiol. 43:3688–3698 [PMC free article] [PubMed]
82. Tankouo-Sandjong B., et al. 2007. MLST-v, multilocus sequence typing based on virulence genes, for molecular typing of Salmonella enterica subsp. enterica serovars. J. Microbiol. Methods 69:23–36 [PubMed]
83. Threlfall E. J., et al. 1999. Pulsed field gel electrophoresis identifies an outbreak of Salmonella enterica serotype Montevideo infection associated with a supermarket hot food outlet. Commun. Dis. Public Health 2:207–209 [PubMed]
84. Tien Y. Y., Wang Y. W., Tung S. K., Liang S. Y., Chiou C. S. 2011. Comparison of multilocus variable-number tandem repeat analysis and pulsed-field gel electrophoresis in molecular subtyping of Salmonella enterica serovars Paratyphi A. Diagn. Microbiol. Infect. Dis. 69:1–6 [PubMed]
85. Torpdahl M., Sorensen G., Lindstedt B. A., Nielsen E. M. 2007. Tandem repeat analysis for surveillance of human Salmonella Typhimurium infections. Emerg. Infect. Dis. 13:388–395 [PMC free article] [PubMed]
86. van Oppen M. J. H. v., Rico C., Turner G. F., Hewitt G. M. 2000. Extensive homoplasy, nonstepwise mutations, and shared ancestral polymorphism at a complex microsatellite locus in Lake Malawi cichlids. Mol. Biol. Evol. 17:489–498 [PubMed]
87. Ward L. R., de Sa J. D., Rowe B. 1987. A phage-typing scheme for Salmonella Enteritidis. Epidemiol. Infect. 99:291–294 [PMC free article] [PubMed]
88. Wattiau P., Van Hessche M., Schlicker C., Vander Veken H., Imberechts H. 2008. Comparison of classical serotyping and PremiTest assay for routine identification of common Salmonella enterica serovars. J. Clin. Microbiol. 46:4037–4040 [PMC free article] [PubMed]
89. Weide-Botjes M., Kobe B., Lange C., Schwarz S. 1998. Molecular typing of Salmonella enterica subsp. enterica serovar Hadar: evaluation and application of different typing methods. Vet. Microbiol. 61:215–227 [PubMed]
90. Weill F. X., Fabre-Berland L., Guibert V., Diancourt L., Brisse S. September 2009. Molecular typing and subtyping of Salmonella by identification of the variable nucleotide sequence of the CRISPR loci. French patent WO 2009/115861
91. Witonski D., et al. 2006. Variable-number tandem repeats that are useful in genotyping isolates of Salmonella enterica subsp. enterica serovars Typhimurium and Newport. J. Clin. Microbiol. 44:3849–3854 [PMC free article] [PubMed]
92. Yoshida C., et al. 2007. Methodologies towards the development of an oligonucleotide microarray for determination of Salmonella serotypes. J. Microbiol. Methods 70:261–271 [PubMed]

Articles from Applied and Environmental Microbiology are provided here courtesy of American Society for Microbiology (ASM)
PubReader format: click here to try

Formats:

Related citations in PubMed

See reviews...See all...

Cited by other articles in PMC

See all...

Links

Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...