Enhancing genomics-based outbreak detection of endemic Salmonella enterica serovar Typhimurium using dynamic thresholds

Closing the gap: Oxford Nanopore Technologies R10 sequencing allows comparable results to Illumina sequencing for SNP-based outbreak investigation of bacterial pathogens

Whole-genome sequencing has become the method of choice for bacterial outbreak investigation, with most clinical and public health laboratories currently routinely using short-read Illumina sequencing. Recently, long-read Oxford Nanopore Technologies (ONT) sequencing has gained prominence and may offer advantages over short-read sequencing, particularly with the recent introduction of the R10 chemistry, which promises much lower error rates than the R9 chemistry. However, limited information is available on its performance for bacterial single-nucleotide polymorphism (SNP)-based outbreak investigation. We present an open-source workflow, Prokaryotic Awesome variant Calling Utility (PACU) (https://github.com/BioinformaticsPlatformWIV-ISP/PACU), for constructing SNP phylogenies using Illumina and/or ONT R9/R10 sequencing data. The workflow was evaluated using outbreak data sets of Shiga toxin-producing Escherichia coli and Listeria monocytogenes by comparing ONT R9 and R10 with Illumina data. The performance of each sequencing technology was evaluated not only separately but also by integrating samples sequenced by different technologies/chemistries into the same phylogenomic analysis. Additionally, the minimum sequencing time required to obtain accurate phylogenetic results using nanopore sequencing was evaluated. PACU allowed accurate identification of outbreak clusters for both species using all technologies/chemistries, but ONT R9 results deviated slightly more from the Illumina results. ONT R10 results showed trends very similar to Illumina, and we found that integrating data sets sequenced by either Illumina or ONT R10 for different isolates into the same analysis produced stable and highly accurate phylogenomic results. The resulting phylogenies for these two outbreaks stabilized after ~20 hours of sequencing for ONT R9 and ~8 hours for ONT R10. This study provides a proof of concept for using ONT R10, either in isolation or in combination with Illumina, for rapid and accurate bacterial SNP-based outbreak investigation.

Nanopore Electrochemistry for Pathogen Detection

Pathogen infections have seriously threatened human health, and there is an urgent demand for rapid and efficient pathogen identification to provide instructions in clinical diagnosis and therapeutic intervention. Recently, nanopore technology, a rapidly maturing technology which delivers ultrasensitive sensing and high throughput in real-time and at low cost, has achieved success in pathogen detection. Furthermore, the remarkable development of nanopore sequencing, for example, the MinION sequencer from Oxford Nanopore Technologies (ONT) as a competitive sequencing technology, has facilitated the rapid analysis of disease-related microbiomes at the whole-genome level and on a large scale. Here, we highlighted recent advances in nanopore approaches for pathogen detection at the single-molecule level. We also overviewed the applications of nanopore sequencing in pathogenic bacteria identification and diagnosis. In the end, we discussed the challenges and future developments of nanopore technology as promising tools for the management of infections, which may be helpful to aid understanding as well as decision-making.

Through the Looking Glass: Genome, Phenome, and Interactome of Salmonella enterica

This review revisits previous concepts on biological phenomenon contributing to the success of the Salmonella enterica subspecies I as a pathogen and expands upon them to include progress in epidemiology based on whole genome sequencing (WGS). Discussion goes beyond epidemiological uses of WGS to consider how phenotype, which is the biological character of an organism, can be correlated with its genotype to develop a knowledge of the interactome. Deciphering genome interactions with proteins, the impact of metabolic flux, epigenetic modifications, and other complex biochemical processes will lead to new therapeutics, control measures, environmental remediations, and improved design of vaccines.

Phase variation in the glycosyltransferase genes of Pasteurella multocida associated with outbreaks of fowl cholera on free-range layer farms

Fowl cholera caused by Pasteurella multocida has re-emerged in Australian poultry production since the increasing adoption of free-range production systems. Currently, autogenous killed whole-cell vaccines prepared from the isolates previously obtained from each farm are the main preventative measures used. In this study, we use whole-genome sequencing and phylogenomic analysis to investigate outbreak dynamics, as well as monitoring and comparing the variations in the lipopolysaccharide (LPS) outer core biosynthesis loci of the outbreak and vaccine strains. In total, 73 isolates from two different free-range layer farms were included. Our genomic analysis revealed that all investigated isolates within the two farms (layer A and layer B) carried LPS type L3, albeit with a high degree of genetic diversity between them. Additionally, the isolates belonged to five different sequence types (STs), with isolates belonging to ST9 and ST20 being the most prevalent. The isolates carried ST-specific mutations within their LPS type L3 outer core biosynthesis loci, including frameshift mutations in the outer core heptosyltransferase gene (htpE) (ST7 and ST274) or galactosyltransferase gene (gatG) (ST20). The ST9 isolates could be separated into three groups based on their LPS outer core biosynthesis loci sequences, with evidence for potential phase variation mechanisms identified. The potential phase variation mechanisms included a tandem repeat insertion in natC and a single base deletion in a homopolymer region of gatG. Importantly, our results demonstrated that two of the three ST9 groups shared identical rep-PCR (repetitive extragenic palindromic PCR) patterns, while carrying differences in their LPS outer core biosynthesis loci region. In addition, we found that ST9 isolates either with or without the natC tandem repeat insertion were both associated with a single outbreak, which would indicate the importance of screening more than one isolate within an outbreak. Our results strongly suggest the need for a metagenomics culture-independent approach, as well as a genetic typing scheme for LPS, to ensure an appropriate vaccine strain with a matching predicted LPS structure is used.

Using whole-genome sequencing to assess the diversity of Paenibacillus larvae within an outbreak and a beekeeping operation

The spore-forming bacterium Paenibacillus larvae is the causative agent of American foulbrood (AFB), a devastating disease of honeybees (Apis mellifera). In the present study, we used whole-genome sequencing (WGS) to investigate an extensive outbreak of AFB in northwestern Slovenia in 2019. A total of 59 P . larvae isolates underwent WGS, of which 40 originated from a single beekeeping operation, to assess the diversity of P. larvae within the beekeeping operation, apiary and colony. By applying a case-specific single-linkage threshold of 34 allele differences (AD), whole-genome multilocus sequence typing (wgMLST) identified two outbreak clusters represented by ERIC II-ST11 clones. All isolates from a single beekeeping operation fell within cluster 1 and the median pairwise AD between them was 10 (range=1–22). The median pairwise AD for apiaries of the same beekeeping operation ranged from 8 to 11 (min.=1, max.=22). For colonies of the same apiary and honey samples from these colonies, the median pairwise AD ranged from 8 to 14 (min.=1, max.=20). The maximum within-cluster distance was 33 pairwise AD for cluster 1 and 44 for cluster 2 isolates. The minimum distance between the outbreak-related and non-related isolates was 37 AD, confirming the importance of associated epidemiological data for delineating outbreak clusters. The observed transmission events could be explained by the activities of honeybees and beekeepers. The present study provides insight into the genetic diversity of P. larvae at different levels and thus provides information for future AFB surveillance.

Elucidation of global and national genomic epidemiology of Salmonella enterica serovar Enteritidis through multilevel genome typing

Salmonella enterica serovar Enteritidis is a major cause of foodborne Salmonella infections and outbreaks in humans. Effective surveillance and timely outbreak detection are essential for public health control. Multilevel genome typing (MGT) with multiple levels of resolution has been previously demonstrated as a promising tool for this purpose. In this study, we developed MGT with nine levels for S. Enteritidis and characterised the genomic epidemiology of S. Enteritidis in detail. We examined 26 670 publicly available S. Enteritidis genome sequences from isolates spanning 101 years from 86 countries to reveal their spatial and temporal distributions. Using the lower resolution MGT levels, globally prevalent and regionally restricted sequence types (STs) were identified; avian associated MGT4-STs were found that were common in human cases in the USA; temporal trends were observed in the UK with MGT5-STs from 2014 to 2018 revealing both long lived endemic STs and the rapid expansion of new STs. Using MGT3 to MGT6, we identified multidrug resistance (MDR) associated STs at various MGT levels, which improves precision of detection and global tracking of MDR clones. We also found that the majority of the global S. Enteritidis population fell within two predominant lineages, which had significantly different propensity of causing large scale outbreaks. An online open MGT database has been established for unified international surveillance of S. Enteritidis. We demonstrated that MGT provides a flexible and high-resolution genome typing tool for S. Enteritidis surveillance and outbreak detection.

Rapid nanopore-based DNA sequencing protocol of antibiotic-resistant bacteria for use in surveillance and outbreak investigation

Outbreak investigations are essential to control and prevent the dissemination of pathogens. This study developed and validated a complete analysis protocol for faster and more accurate surveillance and outbreak investigations of antibiotic-resistant microbes based on Oxford Nanopore Technologies (ONT) DNA whole-genome sequencing. The protocol was developed using 42 methicillin-resistant Staphylococcus aureus (MRSA) isolates identified from former well-characterized outbreaks. The validation of the protocol was performed using Illumina technology (MiSeq, Illumina). Additionally, a real-time outbreak investigation of six clinical S. aureus isolates was conducted to test the ONT-based protocol. The suggested protocol includes: (1) a 20 h sequencing run; (2) identification of the sequence type (ST); (3) de novo genome assembly; (4) polishing of the draft genomes; and (5) phylogenetic analysis based on SNPs. After the sequencing run, it was possible to identify the ST in 2 h (20 min per isolate). Assemblies were achieved after 4 h (40 min per isolate) while the polishing was carried out in 7 min per isolate (42 min in total). The phylogenetic analysis took 0.6 h to confirm an outbreak. Overall, the developed protocol was able to at least discard an outbreak in 27 h (mean) after the bacterial identification and less than 33 h to confirm it. All these estimated times were calculated considering the average time for six MRSA isolates per sequencing run. During the real-time S. aureus outbreak investigation, the protocol was able to identify two outbreaks in less than 31 h. The suggested protocol enables identification of outbreaks in early stages using a portable and low-cost device along with a streamlined downstream analysis, therefore having the potential to be incorporated in routine surveillance analysis workflows. In addition, further analysis may include identification of virulence and antibiotic resistance genes for improved pathogen characterization.

Evaluation of an ensemble-based distance statistic for clustering MLST datasets using epidemiologically defined clusters of cyclosporiasis

Outbreaks of cyclosporiasis, a food-borne illness caused by the coccidian parasite Cyclospora cayetanensis have increased in the USA in recent years, with approximately 2300 laboratory-confirmed cases reported in 2018. Genotyping tools are needed to inform epidemiological investigations, yet genotyping Cyclospora has proven challenging due to its sexual reproductive cycle which produces complex infections characterized by high genetic heterogeneity. We used targeted amplicon deep sequencing and a recently described ensemble-based distance statistic that accommodates heterogeneous (mixed) genotypes and specimens with partial genotyping data, to genotype and cluster 648 C. cayetanensis samples submitted to CDC in 2018. The performance of the ensemble was assessed by comparing ensemble-identified genetic clusters to analogous clusters identified independently based on common food exposures. Using these epidemiologic clusters as a gold standard, the ensemble facilitated genetic clustering with 93.8% sensitivity and 99.7% specificity. Hence, we anticipate that this procedure will greatly complement epidemiologic investigations of cyclosporiasis.

Epidemiology of E. coli in Cystic Fibrosis Airways Demonstrates the Capacity for Persistent Infection but Not Patient-Patient Transmission

Escherichia coli is frequently isolated from the respiratory secretions of cystic fibrosis (CF) patients yet is not considered a classical CF pathogen. Accordingly, little is known about the natural history of this organism in the CF airways, as well as the potential for patient-to-patient transmission. Patients attending the Calgary Adult CF Clinic (CACFC) between January 1983 and December 2016 with at least one E. coli-positive sputum culture were identified by retrospective review. Annual E. coli isolates from the CACFC biobank from each patient were typed by pulsed-field gel electrophoresis (PFGE) and isolates belonging to shared pulsotypes were sequenced. Single nucleotide polymorphism (SNP) and phylogenetic analysis were used to investigate the natural history of E. coli infection and identify potential transmission events. Forty-five patients with E. coli-positive sputum cultures were identified. Most patients had a single infection episode with a single pulsotype, while replacement of an initial pulsotype with a second was observed in three patients. Twenty-four had E. coli recovered from their sputum more than once and 18 patients had persistent infections (E. coli carriage >6 months with ≥3 positive cultures). Shared pulsotypes corresponded to known extraintestinal pathogenic E. coli strains: ST-131, ST-73, and ST-1193. Phylogenetic relationships and SNP distances among isolates within shared pulsotypes were consistent with independent acquisition of E. coli by individual patients. Most recent common ancestor date estimates of isolates between patients were inconsistent with patient-to-patient transmission. E. coli infection in CF is a dynamic process that appears to be characterized by independent acquisition within our patient population and carriage of unique sets of strains over time by individual patients.