Dataset Information

Comparison of xMAP Salmonella Serotyping Assay With Traditional Serotyping and Discordance Resolution by Whole Genome Sequencing.

ABSTRACT: Salmonella spp. are a major cause of foodborne illness throughout the world. Traditional serotyping by antisera agglutination has been used as a standard identification method for many years but newer nucleic acid-based tests have become available that may provide advantages in workflow and test turnaround time. In this study, we evaluated the Luminex® xMAP® Salmonella Serotyping Assay (SSA), a multiplex nucleic acid test capable of identifying 85% of the most common Salmonella serotypes, in comparison to the traditional serum agglutination test (SAT) on 4 standard strains and 255 isolates from human (224), environmental, and food (31) samples. Of the total of 259 isolates, 256 could be typed by the SSA. Of these, 197 (77.0%) were fully typed and 59 (23.0%) were partially typed. By SAT, 246 of the 259 isolates (95%) were successfully typed. Sixty isolates had discrepant results between SAT and SSA and were resolved using whole genome sequencing (WGS). By SAT, 80.0% (48/60) of the isolates were consistent with WGS while by SSA 91.7% (55/60) were partially consistent with WGS. By serovar, all 30 serovars except one tested were fully or partially typable. The workflow comparison showed that SSA provided advantages over SAT with a hands-on time (HOT) of 3.5 min and total turnaround time (TAT) of 6 h, as compared to 1 h HOT and 2-6 days TAT for SAT. Overall, this study showed that molecular serotyping is promising as a rapid method for Salmonella serotyping with good accuracy for typing most common Salmonella serovars circulating in China.

SUBMITTER: Luo Y

PROVIDER: S-EPMC7504902 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Comparison of xMAP Salmonella Serotyping Assay With Traditional Serotyping and Discordance Resolution by Whole Genome Sequencing.

Luo Yun Y Huang Chen C Ye Julian J Octavia Sophie S Wang Huanying H Dunbar Sherry A SA Jin Dazhi D Tang Yi-Wei YW Lan Ruiting R

Frontiers in cellular and infection microbiology 20200907

Salmonella spp. are a major cause of foodborne illness throughout the world. Traditional serotyping by antisera agglutination has been used as a standard identification method for many years but newer nucleic acid-based tests have become available that may provide advantages in workflow and test turnaround time. In this study, we evaluated the Luminex® xMAP® Salmonella Serotyping Assay (SSA), a multiplex nucleic acid test capable of identifying 85% of the most common Salmonella< ...[more]

PMID: 33014887

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Project description:Until recently, traditional serology and the Kauffmann White Scheme (KWS) have been the gold standard for Salmonella serotyping. Whole Genome Sequencing (WGS) has now emerged as an alternative in this field. Serotype information remains a cornerstone in food safety and public health activities to reduce the burden of salmonellosis. At the same time, recent advances in WGS have improved the ability to perform advanced pathogen characterization while improving trace back investigations to determine the source of foodborne illness during outbreaks. Serovar prediction based on WGS can be performed using in silico data analysis tools. Three such tools have been developed: (a). Salmonella in silico Typing Resource (SISTR), (b). SeqSero, and (c). in silico 7-gene MLST ST (Multilocus Sequence Typing Sub-Typing) which was generated using the SISTR platform. Public health officials around the world are diligently working to validate these tools for replacing traditional surveillance methods to provide a more powerful approach for molecular epidemiology in support of public health investigations. In this study, we report a retrospective analysis of our laboratory inventory of 1,041 Salmonella isolates collected between 1999 and 2017. These isolates are of public health significance since they all came from either food, feed or environmental swabs. They were all serotyped by both traditional serology and WGS using an in silico SeqSero tool for serovar prediction. Both predicted identical Salmonella serotypes in 899 isolates (86.4% of the 1,041 Salmonella isolates). SeqSero assignments differed from traditional serological testing in 80 isolates (7.7%) and no serotype prediction was ascertained from 62 isolates (5.9%). This retrospective study is an excellent example of using WGS and SeqSero as a data analysis tool to predict Salmonella serotypes that can provide numerous advantages including molecular and genetic details regarding the characteristics of the Salmonella isolates compared to traditional KWS serotyping. In conclusion, it is evident that using WGS and in silico tools for Salmonella serotyping might someday replace traditional serotyping.

Project description:Salmonella is one of the most common causes of food-borne diseases worldwide. While Salmonella molecular subtyping by Whole Genome Sequencing (WGS) is increasingly used for outbreak and source tracking investigations, serotyping remains as a first-line characterization of Salmonella isolates. The traditional phenotypic method for serotyping is logistically challenging, as it requires the use of more than 150 specific antisera and well trained personnel to interpret the results. Consequently, it is not a routine method for the majority of laboratories. Several rapid molecular methods targeting O and H loci or surrogate genomic markers have been developed as alternative solutions. With the expansion of WGS, in silico Salmonella serotype prediction using WGS data is available. Here, we compared a microarray method using molecular markers, the Check and Trace Salmonella assay (CTS) and a WGS-based serotype prediction tool that targets molecular determinants of serotype (SeqSero) to the traditional phenotypic method using 100 strains representing 45 common and uncommon serotypes. Compared to the traditional method, the CTS assay correctly serotyped 97% of the strains, four strains gave a double serotype prediction. Among the inconclusive data, one strain was not predicted and two strains were incorrectly identified. SeqSero was evaluated with two versions (SeqSero 1 and the alpha test version of SeqSero 2). The correct antigenic formula was predicted by SeqSero 1 for 96 and 95% of strains using raw reads and assembly, respectively. However, 34 and 33% of these predictions included multiple serotypes by raw reads and assembly. With raw reads, one strain was not identified and three strains were discordant with phenotypic serotyping result. With assembly, three strains were not predicted and two strains were incorrectly predicted. While still under development, SeqSero 2 maintained the accuracy of antigenic formula prediction at 98% and reduced multiple serotype prediction rate to 13%. One strain had no prediction and one strain was incorrectly predicted. Our study indicates that the CTS assay is a good alternative for routine laboratories as it is an easy to use method with a short turn-around-time. SeqSero is a reliable replacement for phenotypic serotyping if WGS is routinely implemented.

Project description:We compared the performance of four open-source in silico Salmonella typing tools (SeqSero, SeqSero2, Salmonella In Silico Typing Resource [SISTR], and Metric Oriented Sequence Typer [MOST]) to assess their potential for replacing laboratory serological testing with serovar predictions from whole-genome sequencing data. We conducted a retrospective analysis of 1,624 Salmonella isolates of 72 serovars submitted to the German National Salmonella Reference Laboratory between 1999 and 2019. All isolates are derived from animal and foodstuff origins. We conducted Illumina short-read sequencing and compared the in silico serovar prediction results with the results of routine laboratory serotyping. We found the best-performing in silico serovar prediction tool to be SISTR, with 94% correctly typed isolates, followed by SeqSero2 (87%), SeqSero (81%), and MOST (79%). Furthermore, we found that mapping-based tools like SeqSero and SeqSero2 (allele mode) were more reliable for the prediction of monophasic variants, while sequence type and cluster-based methods like MOST and SISTR (core-genome multilocus sequence type [cgMLST]), showed greater resilience when confronted with GC-biased sequencing data. We showed that the choice of library preparation kit could substantially affect O antigen detection, due to the low GC content of the wzx and wzy genes. Although the accuracy of computational serovar predictions is still not quite on par with traditional serotyping by Salmonella reference laboratories, the command-line tools investigated in this study perform a rapid, efficient, inexpensive, and reproducible analysis, which can be integrated into in-house characterization pipelines. Based on our results, we find SISTR most suitable for automated, routine serotyping for public health surveillance of SalmonellaIMPORTANCESalmonella spp. are important foodborne pathogens. To reduce the number of infected patients, it is essential to understand which subtypes of the bacteria cause disease outbreaks. Traditionally, characterization of Salmonella requires serological testing, a laboratory method by which Salmonella isolates can be classified into over 2,600 distinct subtypes, called serovars. Due to recent advances in whole-genome sequencing, many tools have been developed to replace traditional testing methods with computational analysis of genome sequences. It is crucial to validate that these tools, many already in use for routine surveillance, deliver accurate and reliable serovar information. In this study, we set out to compare which of the currently available open-source command-line tools is most suitable to replace serological testing. A thorough evaluation of the differing computational approaches is highly important to ensure the backward compatibility of serotyping data and to maintain comparability between laboratories.

Project description:BACKGROUND:Pneumococcal serotype identification is essential to monitor pneumococcal vaccine effectiveness and serotype replacement. Serotyping by conventional serological methods are costly, labour-intensive, and require significant technical expertise. We compared two different molecular methods to serotype pneumococci isolated from the nasopharynx of South African infants participating in a birth cohort study, the Drakenstein Child Health Study, in an area with high 13-valent pneumococcal conjugate vaccine (PCV13) coverage. METHODS:A real-time multiplex PCR (rmPCR) assay detecting 21 different serotypes/-groups and a sequetyping assay, based on the sequence of the wzh gene within the pneumococcal capsular locus, were compared. Forty pneumococcal control isolates, with serotypes determined by the Quellung reaction, were tested. In addition, 135 pneumococcal isolates obtained from the nasopharynx of healthy children were tested by both serotyping assays and confirmed by Quellung testing. Discordant results were further investigated by whole genome sequencing of four isolates. RESULTS:Of the 40 control isolates tested, 25 had a serotype covered by the rmPCR assay. These were all correctly serotyped/-grouped. Sequetyping PCR failed in 7/40 (18%) isolates. For the remaining isolates, sequetyping assigned the correct serotype/-group to 29/33 (88%) control isolates. Of the 132/135 (98%) nasopharyngeal pneumococcal isolates that could be typed, 69/132 (52%) and 112/132 (85%) were assigned the correct serotype/-group by rmPCR and sequetyping respectively. The serotypes of 63/132 (48%) isolates were not included in the rmPCR panel. All except three isolates (serotype 25A and 38) were theoretically amplified and differentiated into the correct serotype/-group with some strains giving ambigous results (serotype 13/20, 17F/33C, and 11A/D/1818F). Of the pneumococcal serotypes detected in this study, 69/91 (76%) were not included in the current PCV13. The most frequently identified serotypes were 11A, 13, 15B/15C, 16F and 10A. CONCLUSION:The rmPCR assay performed well for the 21 serotypes/-groups included in the assay. However, in our study setting, a large proportion of serotypes were not detected by rmPCR. The sequetyping assay performed well, but did misassign specific serotypes. It may be useful for regions where vaccine serotypes are less common, however confirmatory testing is advisable.

Project description:The gold standard method for serotyping Escherichia coli has relied on antisera-based typing of the O- and H-antigens, which is labor intensive and often unreliable. In the post-genomic era, sequence-based assays are potentially faster to provide results, could combine O-serogrouping and H-typing in a single test, and could simultaneously screen for the presence of other genetic markers of interest such as virulence factors. Whole genome sequencing is one approach; however, this method has limited multiplexing capabilities, and only a small fraction of the sequence is informative for subtyping or identifying virulence potential. A targeted, sequence-based assay and accompanying software for data analysis would be a great improvement over the currently available methods for serotyping. The purpose of this study was to develop a high-throughput, molecular method for serotyping E. coli by sequencing the genes that are required for production of O- and H-antigens, as well as to develop software for data analysis and serotype identification. To expand the utility of the assay, targets for the virulence factors, Shiga toxins (stx 1, and stx 2) and intimin (eae) were included. To validate the assay, genomic DNA was extracted from O-serogroup and H-type standard strains and from Shiga toxin-producing E. coli, the targeted regions were amplified, and then sequencing libraries were prepared from the amplified products followed by sequencing of the libraries on the Ion S5™ sequencer. The resulting sequence files were analyzed via the SeroType Caller™ software for identification of O-serogroup, H-type, and presence of stx 1 , stx 2, and eae. We successfully identified 169 O-serogroups and 41 H-types. The assay also routinely detected the presence of stx 1a,c,d (3 of 3 strains), stx 2c-e,g (8 of 8 strains), stx 2f (1 strain), and eae (6 of 6 strains). Taken together, the high-throughput, sequence-based method presented here is a reliable alternative to antisera-based serotyping methods for E. coli.

Dataset Information

Comparison of xMAP Salmonella Serotyping Assay With Traditional Serotyping and Discordance Resolution by Whole Genome Sequencing.

Publications

Comparison of xMAP <i>Salmonella</i> Serotyping Assay With Traditional Serotyping and Discordance Resolution by Whole Genome Sequencing.

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