Classification of Salmonella enterica serotypes from Australian poultry using repetitive sequence-based PCR

Comparison of Whole Genome Sequencing and Repetitive Element PCR for Multidrug- Resistant Pseudomonas aeruginosa Strain Typing

Hospital-acquired infections pose significant costly global challenges to patient care. Rapid and sensitive methods to identify potential outbreaks are integral to infection control measures. Whole genome sequencing (WGS)-based bacterial strain typing provides higher discriminatory power over standard nucleotide banding pattern-based methods like repetitive sequence-based PCR (rep-PCR). However, integration of WGS into clinical epidemiology is limited by the lack of consensus in methodology and data analysis/interpretation. In this study, WGS was performed on 22 multidrug-resistant Pseudomonas aeruginosa (MDR-PA) genomic DNA using the Illumina MiSeq platform. Resulting high quality reads were analyzed for phylogenetic relatedness using whole genome multi-locus sequence typing (wgMLST)-based BIOMÉRIEUX EPISEQ CS (EpiSeq; Durham, NC) and Single Nucleotide Variant PHYLogenomics (SNVPhyl). WGS-based results were compared to conventional MLST and archived rep-PCR results. Rep-PCR identified three independent clonal clusters of MDR-PA. Only one clonal cluster identified by rep-PCR, an endemic strain within the pediatric cystic fibrosis population at Texas Children's Hospital, was concordantly identified using wgMLST (EpiSeq) and SNVPhyl. Results were highly consistent between the three sequence-based analyses (conventional MLST, wgMLST, and SNVPhyl), and these results remained consistent with the addition of 74 MDR-PA genomes. These WGS-based methods provided greater resolution for strain discrimination than rep-PCR or standard MLST classification, and the ease of use of EpiSeq renders it clinically viable for analysis, interpretation, and reporting of WGS-based strain typing.

Assessment and Comparison of Molecular Subtyping and Characterization Methods for Salmonella

The food industry is facing a major transition regarding methods for confirmation, characterization, and subtyping of Salmonella. Whole-genome sequencing (WGS) is rapidly becoming both the method of choice and the gold standard for Salmonella subtyping; however, routine use of WGS by the food industry is often not feasible due to cost constraints or the need for rapid results. To facilitate selection of subtyping methods by the food industry, we present: (i) a comparison between classical serotyping and selected widely used molecular-based subtyping methods including pulsed-field gel electrophoresis, multilocus sequence typing, and WGS (including WGS-based serovar prediction) and (ii) a scoring system to evaluate and compare Salmonella subtyping assays. This literature-based assessment supports the superior discriminatory power of WGS for source tracking and root cause elimination in food safety incident; however, circumstances in which use of other subtyping methods may be warranted were also identified. This review provides practical guidance for the food industry and presents a starting point for further comparative evaluation of Salmonella characterization and subtyping methods.

Empirical testing of modified Salmonella MLST in aquatic environmental samples by in silico analysis

Multilocus sequence typing (MLST) is an approach for prediction of Salmonella servoar and eBRUST groups (eBGs) based on seven typing scheme of housekeeping genes. Up to date, >220.000 allelic profiles and 65,973 Salmonella strains have been established in the MLST database. Several studies have modified MLST method with fewer targeted housekeeping genes for the purpose of economy and efficiency. Nevertheless, no study has conducted systematically to evaluate the correlation between the numbers of housekeeping genes targeted and the accuracy of prediction rate. In this study, we aimed to tackle this problem by extracting data from the MLST database as a whole using the software RStudio. Our results indicated that as the numbers of genes in MLST scheme increased, the accuracy of the eBGs prediction rate increased and reached 100% when the gene numbers are greater than or equal to 5. To examine the applicability of the approach, 395 environmental water samples were subjected to this study. A set of 52 Salmonella enterica isolates was initially used to develop MLST targeting seven housekeeping genes. A total of 29 sequence types, including 11 new sequence types were found among the 52 sequenced isolates that differentiated into 19 serotypes. Moreover, two novel sequence types did not belong to current classification. Our results show that the outcome in the three-gene sequence typing (aroC, hisD, and purE) was as accurate as in the seven-gene sequence typing for prediction of environmental Salmonella isolates. Our data suggested that this five-gene and reduced gene-number sequence-typing scheme can serve as an alternative modified MLST when effectiveness and financial management were the concerns.

Worldwide Lineages of Clinical Pneumococci in a Japanese Teaching Hospital Identified by DiversiLab System

Pneumococcal Molecular Epidemiology Network (PMEN) clones are representatives of worldwide-spreading pathogens. DiversiLab system, a repetitive PCR system, has been proposed as a less labor-and time-intensive genotyping platform alternative to conventional methods. However, the utility and analysis parameters of DiversiLab for identifying worldwide lineages was not established. To evaluate and optimize the performance of DiversiLab for identifying worldwide pneumococcal lineages, we examined 245 consecutive isolates of clinical Streptococcus pneumoniae from all age-group patients at a teaching hospital in Japan. The capsular swelling reaction of all isolates yielded 24 different serotypes. Intensive visual observation (VO) of DiversiLab band pattern difference divided all isolates into 73 clusters. Multilocus sequence typing (MLST) of representative 73 isolates from each VO cluster yielded 51 different STs. Among them, PMEN-related lineages accounted for 63% (46/73). Although the serotype of PMEN-related isolates was identical to that of the original PMEN clone in 70% (32/46), CC156-related PMEN lineages, namely Greece(6B)-22 and Colombia(23F)-26, harbored various capsular types discordant to the original PMEN clones. Regarding automated analysis, genotyping by extended Jaccard (XJ) with a 75% similarity index cutoff (SIC) showed the highest correlation with serotyping (adjusted Rand's coefficient, 0.528). Elevating the SIC for XJ to 85% increased the discriminatory power sufficient for distinguishing two major PMEN-related isolates of Taiwan(19F)-14 and Netherlands(3)-31. These results demonstrated a potential utility of DiversiLab for identifying worldwide lineage of pneumococcus. An optimized parameters of automated analysis should be useful especially for comparison for reference strains by "identification" function of DiversiLab.

Molecular Subtyping of Shiga Toxin-Producing Escherichia coli Using a Commercial Repetitive Sequence-Based PCR Assay

PCR-based typing methods, such as repetitive sequence-based PCR (rep-PCR), may facilitate the identification of Shiga toxin-producing Escherichia coli (STEC) by serving as screening methods to reduce the number of isolates to be processed for further confirmation. In this study, we used a commercial rep-PCR typing system to generate DNA fingerprint profiles for STEC O157 (n = 60) and non-O157 (n = 91) isolates from human, food, and animal samples and then compared the results with those obtained from pulsed-field gel electrophoresis (PFGE). Fifteen serogroups were analyzed using the Kullback Leibler or extended Jaccard statistical method, and the unweighted pair group method of averages algorithm was used to create dendrograms. Among the 151 STEC isolates tested, all were typeable by rep-PCR. Among the non-O157 isolates, rep-PCR clustered 79 (88.8%) of 89 isolates according to serogroup status, with peak differences ranging from 1 (96.4% similarity) to 12 (58.7% similarity). The genetic relatedness of the non-O157 serogroups mirrored the branching of distinct clonal groups elucidated by other investigators. Although the discriminatory power of rep-PCR (Simpson's index of diversity [SID] = 0.954) for the O157 isolates was less than that of PFGE (SID = 0.993), rep-PCR was able to identify 29 pattern types, suggesting that this method can be used for strain typing, although not to the same level as PFGE. Similar results were obtained from analysis of the non-O157 isolates. With rep-PCR, we assigned non-O157 isolates to 46 pattern types with a SID of 0.977. By PFGE, non-O157 STEC strains were divided into 77 pattern types with a SID of 0.996. Together, these results indicate the ability of the rep-PCR typing system to distinguish between and within O157 and non-O157 STEC groups. Rapid PCR-based typing methods could be invaluable tools for use in outbreak investigations by excluding unrelated STEC isolates within 24 h.

Molecular methods for serovar determination of Salmonella

Salmonella is a diverse foodborne pathogen, which has more than 2600 recognized serovars. Classification of Salmonella isolates into serovars is essential for surveillance and epidemiological investigations; however, determination of Salmonella serovars, by traditional serotyping, has some important limitations (e.g. labor intensive, time consuming). To overcome these limitations, multiple methods have been investigated to develop molecular serotyping schemes. Currently, molecular methods to predict Salmonella serovars include (i) molecular subtyping methods (e.g. PFGE, MLST), (ii) classification using serovar-specific genomic markers and (iii) direct methods, which identify genes encoding antigens or biosynthesis of antigens used for serotyping. Here, we reviewed reported methodologies for Salmonella molecular serotyping and determined the "serovar-prediction accuracy", as the percentage of isolates for which the serovar was correctly classified by a given method. Serovar-prediction accuracy ranged from 0 to 100%, 51 to 100% and 33 to 100% for molecular subtyping, serovar-specific genomic markers and direct methods, respectively. Major limitations of available schemes are errors in predicting closely related serovars (e.g. Typhimurium and 4,5,12:i:-), and polyphyletic serovars (e.g. Newport, Saintpaul). The high diversity of Salmonella serovars represents a considerable challenge for molecular serotyping approaches. With the recent improvement in sequencing technologies, full genome sequencing could be developed into a promising molecular approach to serotype Salmonella.

Salmonella enterica diversity in central Californian coastal waterways

Salmonella enterica is one of the most important bacterial enteric pathogens worldwide. However, little is known about its distribution and diversity in the environment. The present study explored the diversity of 104 strains of Salmonella enterica isolated over 2 years from 12 coastal waterways in central California. Pulsed-field gel electrophoresis (PFGE) and multilocus sequence typing were used to probe species diversity. Seventy-four PFGE patterns and 38 sequence types (STs) were found, including 18 newly described STs. Nineteen of 25 PFGE patterns were indistinguishable from those of clinical isolates in PulseNet. The most common ST was consistent with S. enterica serovar Typhimurium, and other frequently detected STs were associated with the serovars Heidelberg and Enteritidis; all of these serovars are important etiologies of salmonellosis. An investigation into S. enterica biogeography was conducted at the level of ST and subspecies. At the ST and subspecies level, we found a taxon-time relationship but no taxon-area or taxon-environmental distance relationships. STs collected during wet versus dry conditions tended to be more similar; however, STs collected from waterways adjacent to watersheds with similar land covers did not tend to be similar. The results suggest that the lack of dispersal limitation may be an important factor affecting the diversity of S. enterica in the region.

Comparison of typing methods with a new procedure based on sequence characterization for Salmonella serovar prediction

As the development of molecular serotyping approaches is critical for Salmonella spp., which include >2,600 serovars, we performed an initial evaluation of the ability to identify Salmonella serovars using (i) different molecular subtyping methods and (ii) a newly implemented combined PCR- and sequencing-based approach that directly targets O- and H-antigen-encoding genes. Initial testing was performed using 46 isolates that represent the top 40 Salmonella serovars isolated from human and nonhuman sources, as reported by the U.S. Centers for Disease Control and Prevention and the World Health Organization. Multilocus sequence typing (MLST) was able to accurately predict the serovars for 42/46 isolates and showed the best ability to predict serovars among the subtyping methods tested. Pulsed-field gel electrophoresis (PFGE), ribotyping, and repetitive extragenic palindromic sequence-based PCR (rep-PCR) were able to accurately predict the serovars for 35/46, 34/46, and 30/46 isolates, respectively. Among the methods, S. enterica subsp. enterica serovars 4,5,12:i:-, Typhimurium, and Typhimurium var. 5- were frequently not classified correctly, which is consistent with their close phylogenetic relationship. To develop a PCR- and sequence-based serotyping approach, we integrated available data sources to implement a combination PCR-based O-antigen screening and sequencing of internal fliC and fljB fragments. This approach correctly identified the serovars for 42/46 isolates in the initial set representing the most common Salmonella serovars, as well as for 54/63 isolates representing less common Salmonella serovars. Our study not only indicates that different molecular approaches show the potential to allow for rapid serovar classification of Salmonella isolates, but it also provides data that can help with the selection of molecular serotyping methods to be used by different laboratories.