Genomic tracing of epidemics and disease outbreaks

Forensic Microbiology: When, Where and How

Forensic microbiology is a relatively new discipline, born in part thanks to the development of advanced methodologies for the detection, identification and characterization of microorganisms, and also in relation to the growing impact of infectious diseases of iatrogenic origin. Indeed, the increased application of medical practices, such as transplants, which require immunosuppressive treatments, and the growing demand for prosthetic installations, associated with an increasing threat of antimicrobial resistance, have led to a rise in the number of infections of iatrogenic origin, which entails important medico-legal issues. On the other hand, the possibility of detecting minimal amounts of microorganisms, even in the form of residual traces (e.g., their nucleic acids), and of obtaining gene and genomic sequences at contained costs, has made it possible to ask new questions of whether cases of death or illness might have a microbiological origin, with the possibility of also tracing the origin of the microorganisms involved and reconstructing the chain of contagion. In addition to the more obvious applications, such as those mentioned above related to the origin of iatrogenic infections, or to possible cases of infections not properly diagnosed and treated, a less obvious application of forensic microbiology concerns its use in cases of violence or violent death, where the characterization of the microorganisms can contribute to the reconstruction of the case. Finally, paleomicrobiology, e.g., the reconstruction and characterization of microorganisms in historical or even archaeological remnants, can be considered as a sister discipline of forensic microbiology. In this article, we will review these different aspects and applications of forensic microbiology.

Defining genomic epidemiology thresholds for common-source bacterial outbreaks: a modelling study

BACKGROUND

Epidemiological surveillance relies on microbial strain typing, which defines genomic relatedness among isolates to identify case clusters and their potential sources. Although predefined thresholds are often applied, known outbreak-specific features such as pathogen mutation rate and duration of source contamination are rarely considered. We aimed to develop a hypothesis-based model that estimates genetic distance thresholds and mutation rates for point-source single-strain food or environmental outbreaks.

METHODS

In this modelling study, we developed a forward model to simulate bacterial evolution at a specific mutation rate (μ) over a defined outbreak duration (D). From the distribution of genetic distances expected under the given outbreak parameters and sample isolation dates, we estimated a distance threshold beyond which isolates should not be considered as part of the outbreak. We embedded the model into a Markov Chain Monte Carlo inference framework to estimate the most probable mutation rate or time since source contamination, which are both often imprecisely documented. A simulation study validated the model over realistic durations and mutation rates. We then identified and analysed 16 published datasets of bacterial source-related outbreaks; datasets were included if they were from an identified foodborne outbreak and if whole-genome sequence data and collection dates for the described isolates were available.

FINDINGS

Analysis of simulated data validated the accuracy of our framework in both discriminating between outbreak and non-outbreak cases and estimating the parameters D and μ from outbreak data. Precision of estimation was much higher for high values of D and μ. Sensitivity of outbreak cases was always very high, and specificity in detecting non-outbreak cases was poor for low mutation rates. For 14 of the 16 outbreaks, the classification of isolates as being outbreak-related or sporadic is consistent with the original dataset. Four of these outbreaks included outliers, which were correctly classified as being beyond the threshold of exclusion estimated by our model, except for one isolate of outbreak 4. For two outbreaks, both foodborne Listeria monocytogenes, conclusions from our model were discordant with published results: in one outbreak two isolates were classified as outliers by our model and in another outbreak our algorithm separated food samples into one cluster and human samples into another, whereas the isolates were initially grouped together based on epidemiological and genetic evidence. Re-estimated values of the duration of outbreak or mutation rate were largely consistent with a priori defined values. However, in several cases the estimated values were higher and improved the fit with the observed genetic distance distribution, suggesting that early outbreak cases are sometimes missed.

INTERPRETATION

We propose here an evolutionary approach to the single-strain conundrum by estimating the genetic threshold and proposing the most probable cluster of cases for a given outbreak, as determined by its particular epidemiological and microbiological properties. This forward model, applicable to foodborne or environmental-source single point case clusters or outbreaks, is useful for epidemiological surveillance and may inform control measures.

FUNDING

European Union Horizon 2020 Research and Innovation Programme.

Emergence and Molecular Epidemiology of Campylobacter jejuni ST-2993 Associated with a Large Outbreak of Guillain-Barré Syndrome in Peru

Campylobacter jejuni infection is considered the most frequent factor associated with Guillain-Barré syndrome (GBS). In 2019, a large outbreak of GBS was detected in Peru, being associated with C. jejuni detected in stool samples from these patients. The aim of this study was to determine the molecular epidemiology of C. jejuni strains (ST-2993) associated with a large GBS outbreak in Peru. In this study, 26 C. jejuni strains belonging to the ST-2293, obtained from 2019 to 2020, were sequenced using Illumina technology. Five low-quality sequences were removed using bioinformatics, and 21 genomes (17 clinical strains and 4 chicken strains) were considered in the phylogenetic analysis and comparative genomics. Phylogenetic reconstruction, including genomes from international databases, showed a connection between Peruvian and Chinese GBS strains, both of them having lipooligosaccharides (LOS) locus genes related to molecular mimicry with gangliosides in peripheral nerves. Also, ST-2993 was detected in Amazon strains recovered many years before the 2019 outbreak, but with no epidemiological connection with GBS. Besides, a close relationship between human and chicken C. jejuni strains indicated chicken as one of the probable reservoirs. Finally, comparative genomics revealed differences between Chinese and Peruvian strains, including the presence of a prophage inserted into the genome. In conclusion, C. jejuni ST-2993 strains recovered from the GBS outbreak are closely related to Peruvian Amazon strains. Moreover, ST-2993 has been circulated in Peru since 2003 in the Peruvian Amazonia, showing the necessity to reinforce the epidemiological surveillance of C. jejuni to improve the prevention and control of future GBS outbreaks. IMPORTANCE This article describes the molecular epidemiology of C. jejuni strains (ST-2993) associated with a large Guillain-Barré Syndrome (GBS) outbreak in Peru, sequencing several strains recovered from GBS patients and chickens from 2019 to 2020. Phylogenetic analysis showed a connection between Peruvian and Chinese GBS strains, both of them having lipooligosaccharides (LOS) locus genes related to molecular mimicry with gangliosides in peripheral nerves. Also, ST-2993 strains were detected in isolates recovered many years before the 2019 outbreak, but with no epidemiological connection with GBS. Besides, a close relationship between human and chicken strains indicated those animals as a probable reservoir. This information will help to understand the real situation of GBS in Peru and its causal agent, C. jejuni ST-2993, showing the necessity to increase epidemiological tracking of these kinds of pathogens to detect them and avoid GBS outbreaks in the future.

Whole-genome sequence analysis through online web interfaces: a review

The recent development of whole-genome sequencing technologies paved the way for understanding the genomes of microorganisms. Every whole-genome sequencing (WGS) project requires a considerable cost and a massive effort to address the questions at hand. The final step of WGS is data analysis. The analysis of whole-genome sequence is dependent on highly sophisticated bioinformatics tools that the research personal have to buy. However, many laboratories and research institutions do not have the bioinformatics capabilities to analyze the genomic data and therefore, are unable to take maximum advantage of whole-genome sequencing. In this aspect, this study provides a guide for research personals on a set of bioinformatics tools available online that can be used to analyze whole-genome sequence data of bacterial genomes. The web interfaces described here have many advantages and, in most cases exempting the need for costly analysis tools and intensive computing resources.

Molecular Epidemiology of Xanthomonas perforans Outbreaks in Tomato Plants from Transplant to Field as Determined by Single-Nucleotide Polymorphism Analysis

Outbreaks of bacterial spot on tomato (BST) caused by Xanthomonas perforans are a major concern for sustainable crop production. BST is a common occurrence in tomato transplants grown for field production. We hypothesized that BST outbreaks in commercial fields originate from X. perforans strains inadvertently introduced from commercial transplant facilities. To test this hypothesis, we used a genome-wide single-nucleotide polymorphism (SNP) analysis to characterize X. perforans strains recovered from tomato transplant facilities and fields in commercial production areas. X. perforans strains were isolated from symptomatic transplants prior to roguing at two commercial transplant growers. Then, the same groups of transplants were tracked to commercial fields to recover X. perforans strains from diseased plants prior to harvest. Whole-genome sequencing was carried out on 84 strains isolated from transplant and field plants from Florida and South Carolina. SNPs were called using three reference strains that represented the genetic variation of the sampled strains. Field strains showing genetic similarity to transplant strains had a difference of 2 to 210 SNPs. Transplant and field strains clustered together by grower within each phylogenomic group, consistent with expectations. The range of genetic divergence among strains isolated from field plants was similar to the range obtained from strains on transplants. Using the range of genetic variation observed in transplants, we estimate that 60% to 100% of field strains were an extension of the transplant strain population. Our results stress the importance of BST management to reduce X. perforans movement from transplant to field and to minimize subsequent disease outbreaks.IMPORTANCE Current management of Xanthomonas perforans on tomato plants mainly relies on the frequent application of pesticides. However, the lack of effective pesticides and the development of strain tolerance to certain bactericides limit the ability to control outbreaks in production fields. Better knowledge of probable sources of X. perforans inoculum during tomato production is required to refine management strategies. Tomato plants are typically established in the field using transplants. This study aimed to determine if strains from field epidemics were coming from transplant facilities or resulted from local field outbreaks. The overall goal was to identify potential sources of inoculum and subsequently develop strategies to reduce carryover from transplant production to the field. Our results indicate that tomato producers should shift disease management efforts to transplant facilities to reduce disease in the field. Improved transplant health should reduce the likelihood of bacterial spot outbreaks and subsequently reduce pesticide usage in the field.

Microbial forensics: new breakthroughs and future prospects

Recent advances in genetic data generation, through massive parallel sequencing (MPS), storage and analysis have fostered significant progresses in microbial forensics (or forensic microbiology). Initial applications in circumstances of biocrime, bioterrorism and epidemiology are now accompanied by the prospect of using microorganisms (i) as ancillary evidence in criminal cases; (ii) to clarify causes of death (e.g., drownings, toxicology, hospital-acquired infections, sudden infant death and shaken baby syndromes); (iii) to assist human identification (skin, hair and body fluid microbiomes); (iv) for geolocation (soil microbiome); and (v) to estimate postmortem interval (thanatomicrobiome and epinecrotic microbial community). When compared with classical microbiological methods, MPS offers a diverse range of advantages and alternative possibilities. However, prior to its implementation in the forensic context, critical efforts concerning the elaboration of standards and guidelines consolidated by the creation of robust and comprehensive reference databases must be undertaken.

Comparison of whole genome sequencing to restriction endonuclease analysis and gel diffusion precipitin-based serotyping of Pasteurella multocida

The gel diffusion precipitin test (GDPT) and restriction endonuclease analysis (REA) have commonly been used in the serotyping and genotyping of Pasteurella multocida. Whole genome sequencing (WGS) and single nucleotide polymorphism (SNP) analysis has become the gold standard for other organisms, offering higher resolution than previously available methods. We compared WGS to REA and GDPT on 163 isolates of P. multocida to determine if WGS produced more precise results. The isolates used represented the 16 reference serovars, isolates with REA profiles matching an attenuated fowl cholera vaccine strain, and isolates from 10 different animal species. Isolates originated from across the United States and from Chile. Identical REA profiles clustered together in the phylogenetic tree. REA profiles that differed by only a few bands had fewer SNP differences than REA profiles with more differences, as expected. The GDPT results were diverse but it was common to see a single serovar show up repeatedly within clusters. Several errors were found when examining the REA profiles. WGS was able to confirm these errors and compensate for the subjectivity in analysis of REA. Also, results of WGS and SNP analysis correlated more closely with the epidemiologic data than GDPT. In silico results were also compared to a lipopolysaccharide rapid multiplex PCR test. From the data produced in our study, WGS and SNP analysis was superior to REA and GDPT and highlighted some of the issues with the older tests.

Salmonella Thompson outbreak associated with consumption of chicken shawarma and the usefulness of genome sequencing in the investigation

Background

A sudden increase in Salmonella Thompson (S. Thompson) cases distributed throughout three border regions in the province of Quebec in November 2016 triggered a provincial investigation to identify a common source of contamination and to put the appropriate control measures into place.

Objective

To report on the outbreak and to describe the use of genomic sequencing to identify the salmonella serotype responsible.

Methods

A descriptive survey of all reported cases of Salmonella serogroup C1 that had occurred between October 1, 2016 and February 15, 2017 was conducted. A case definition was developed. Pulsed field gel electrophoresis supplemented by analyses of genome sequences using the single nucleotide variant phylogenomics method were used to demarcate and manage the outbreak.

Results

Eighteen cases of S. Thompson were identified through whole genome sequencing. The onset dates of symptoms for the 16 cases that presented enteric symptoms were November 21-December 2, 2016. Two cases that presented with atypical symptoms were not reported until February 2017. Among the 18 cases, 16 had eaten or probably eaten chicken shawarma at the same restaurant chain and nine of these cases ate it at the same restaurant. In total, five restaurants from this chain, spread throughout three border regions of Quebec, were identified.

Conclusion

Outbreaks associated with chicken shawarma have been identified in the past. Efforts must be made to ensure that the owners of this type of restaurant know the contamination risk associated with this type of cooking and take the necessary steps to reduce this risk. The use of the genome sequencing method was very useful in defining the outbreak.

Diagnostics and Resistance Profiling of Bacterial Pathogens

Worldwide infectious disease is one of the leading causes of death. Despite improvements in technology and healthcare services, morbidity and mortality due to infections have remained unchanged over the past few decades. The high and increasing rate of antibiotic resistance is further aggravating the situation. Growing resistance hampers the use of conventional antibiotics, and substantial higher mortality rates are reported in patients given ineffective empiric therapy mainly due to resistance to the agents used. These infections cause suffering, incapacity, and death and impose an enormous financial burden on both healthcare systems and on society in general. The accelerating development of multidrug resistance is one of the greatest diagnostic and therapeutic challenges to modern medicine. The lack of new antibiotic options underscores the need for optimization of current diagnostics, therapies, and prevention of the spread of multidrug-resistant organisms. The so-called -omics technologies (genomics, transcriptomics, proteomics, and metabolomics) have yielded large-scale datasets that advanced the search for biomarkers of infectious diseases in the last decade. One can imagine that in the future the implementation of biomarker-driven molecular test systems will transform diagnostics of infectious diseases and will significantly accelerate the identification of the bacterial pathogens at the infected host site. Furthermore, molecular tests based on the identification of markers of antibiotic resistance will dramatically change resistance profiling. The replacement of culturing methods by molecular test systems for early diagnosis will provide the basis not only for a prompt and targeted therapy, but also for a much more effective stewardship of antibiotic agents and a reduction of the spread of multidrug resistance as well as the appearance of new antibiotic resistances.

Usefulness of High-Quality Core Genome Single-Nucleotide Variant Analysis for Subtyping the Highly Clonal and the Most Prevalent Salmonella enterica Serovar Heidelberg Clone in the Context of Outbreak Investigations

Salmonella enterica serovar Heidelberg is the second most frequently occurring serovar in Quebec and the third-most prevalent in Canada. Given that conventional pulsed-field gel electrophoresis (PFGE) subtyping for common Salmonella serovars, such as S. Heidelberg, yields identical subtypes for the majority of isolates recovered, public health laboratories are desperate for new subtyping tools to resolve highly clonal S. Heidelberg strains involved in outbreak events. As PFGE was unable to discriminate isolates from three epidemiologically distinct outbreaks in Quebec, this study was conducted to evaluate whole-genome sequencing (WGS) and phylogenetic analysis as an alternative to conventional subtyping tools. Genomes of 46 isolates from 3 Quebec outbreaks (2012, 2013, and 2014) supported by strong epidemiological evidence were sequenced and analyzed using a high-quality core genome single-nucleotide variant (hqSNV) bioinformatics approach (SNV phylogenomics [SNVphyl] pipeline). Outbreaks were indistinguishable by conventional PFGE subtyping, exhibiting the same PFGE pattern (SHEXAI.0001/SHEBNI.0001). Phylogenetic analysis based on hqSNVs extracted from WGS separated the outbreak isolates into three distinct groups, 100% concordant with the epidemiological data. The minimum and maximum number of hqSNVs between isolates from the same outbreak was 0 and 4, respectively, while >59 hqSNVs were measured between 2 previously indistinguishable outbreaks having the same PFGE and phage type, thus corroborating their distinction as separate unrelated outbreaks. This study demonstrates that despite the previously reported high clonality of this serovar, the WGS-based hqSNV approach is a superior typing method, capable of resolving events that were previously indistinguishable using classic subtyping tools.

Characterization of Foodborne Outbreaks of Salmonella enterica Serovar Enteritidis with Whole-Genome Sequencing Single Nucleotide Polymorphism-Based Analysis for Surveillance and Outbreak Detection

Salmonella enterica serovar Enteritidis is a significant cause of gastrointestinal illness in the United States; however, current molecular subtyping methods lack resolution for this highly clonal serovar. Advances in next-generation sequencing technologies have made it possible to examine whole-genome sequencing (WGS) as a potential molecular subtyping tool for outbreak detection and source trace back. Here, we conducted a retrospective analysis of S. Enteritidis isolates from seven epidemiologically confirmed foodborne outbreaks and sporadic isolates (not epidemiologically linked) to determine the utility of WGS to identify outbreaks. A collection of 55 epidemiologically characterized clinical and environmental S. Enteritidis isolates were sequenced. Single nucleotide polymorphism (SNP)-based cluster analysis of the S. Enteritidis genomes revealed well supported clades, with less than four-SNP pairwise diversity, that were concordant with epidemiologically defined outbreaks. Sporadic isolates were an average of 42.5 SNPs distant from the outbreak clusters. Isolates collected from the same patient over several weeks differed by only two SNPs. Our findings show that WGS provided greater resolution between outbreak, sporadic, and suspect isolates than the current gold standard subtyping method, pulsed-field gel electrophoresis (PFGE). Furthermore, results could be obtained in a time frame suitable for surveillance activities, supporting the use of WGS as an outbreak detection and characterization method for S. Enteritidis.