Genotyping genetically heterogeneous Cyclospora cayetanensis infections to complement epidemiological case linkage

Evaluation of the Increased Genetic Resolution and Utility for Source Tracking of a Recently Developed Method for Genotyping Cyclospora cayetanensis

Cyclospora cayetanensis is a foodborne parasite that causes cyclosporiasis, an enteric illness in humans. Genotyping methods are used to genetically discriminate between specimens from cyclosporiasis cases and can complement source attribution investigations if the method is sufficiently sensitive for application to food items. A very sensitive targeted amplicon sequencing (TAS) assay for genotyping C. cayetanensis encompassing 52 loci was recently designed. In this study, we analyzed 66 genetically diverse clinical specimens to assess the change in phylogenetic resolution between the TAS assay and a currently employed eight-marker scheme. Of the 52 markers, ≥50 were successfully haplotyped for all specimens, and these results were used to generate a hierarchical cluster dendrogram. Using a previously described statistical approach to dissect hierarchical trees, the 66 specimens resolved into 24 and 27 distinct genetic clusters for the TAS and an 8-loci scheme, respectively. Although the specimen composition of 15 clusters was identical, there were substantial differences between the two dendrograms, highlighting the importance of both inclusion of additional genome coverage and choice of loci to target for genotyping. To evaluate the ability to genetically link contaminated food samples with clinical specimens, C. cayetanensis was genotyped from DNA extracted from raspberries inoculated with fecal specimens. The contaminated raspberry samples were assigned to clusters with the corresponding clinical specimen, demonstrating the utility of the TAS assay for traceback efforts.

Sapp SG, Peterson A, Qvarnstrom Y. Comparison of two novel one-tube nested real-time qPCR assays to detect human-infecting Cyclospora spp

IMPORTANCE

Human-infecting Cyclospora spp. cause gastrointestinal distress among healthy individuals contributing to morbidity and putting stress on the economics of countries and companies in the form of produce recalls. Accessible and easy-to-use diagnostic tools available to a wide variety of laboratories would aid in the early detection of possible outbreaks of cyclosporiasis. This, in turn, will assist in the timely traceback investigation to the suspected source of an outbreak by informing the smallest possible recall and protecting consumers from contaminated produce. This manuscript describes two novel detection methods with improved performance for the causative agents of cyclosporiasis when compared to the currently used 18S assay.

Evaluation of nuclear and mitochondrial phylogenetics for the subtyping of Cyclospora cayetanensis

Cyclospora cayetanensis is an enteric coccidian parasite responsible for gastrointestinal disease transmitted through contaminated food and water. It has been documented in several countries, mostly with low-socioeconomic levels, although major outbreaks have hit developed countries. Detection methods based on oocyst morphology, staining, and molecular testing have been developed. However, the current MLST panel offers an opportunity for enhancement, as amplification of all molecular markers remains unfeasible in the majority of samples. This study aims to address this challenge by evaluating two approaches for analyzing the genetic diversity of C. cayetanensis and identifying reliable markers for subtyping: core homologous genes and mitochondrial genome analysis. A pangenome was constructed using 36 complete genomes of C. cayetanensis, and a haplotype network and phylogenetic analysis were conducted using 33 mitochondrial genomes. Through the analysis of the pangenome, 47 potential markers were identified, emphasizing the need for more sequence data to achieve comprehensive characterization. Additionally, the analysis of mitochondrial genomes revealed 19 single-nucleotide variations that can serve as characteristic markers for subtyping this parasite. These findings not only contribute to the selection of molecular markers for C. cayetanensis subtyping, but they also drive the knowledge toward the potential development of a comprehensive genotyping method for this parasite.

Novel insights on the genetic population structure of human-infecting Cyclospora spp. and evidence for rapid subtype selection among isolates from the USA

Human-infecting Cyclospora was recently characterized as three species, two of which (C. cayetanensis and C. ashfordi) are currently responsible for all known human infections in the USA, yet much remains unknown about the genetic structure within these two species. Here, we investigate Cyclospora genotyping data from 2018 through 2022 to ascertain if there are temporal patterns in the genetic structure of Cyclospora parasites that cause infections in US residents from year to year. First, we investigate three levels of genetic characterization: species, subpopulation, and strain, to elucidate annual trends in Cyclospora infections. Next, we determine if shifts in genetic diversity can be linked to any of the eight loci used in our Cyclospora genotyping approach. We observed fluctuations in the abundance of Cyclospora types at the species and subpopulation levels, but no significant temporal trends were identified; however, we found recurrent and sporadic strains within both C. ashfordi and C. cayetanensis. We also uncovered major shifts in the mitochondrial genotypes in both species, where there was a universal increase in abundance of a specific mitochondrial genotype that was relatively abundant in 2018 but reached near fixation (was observed in over 96% of isolates) in C. ashfordi by 2022. Similarly, this allele jumped from 29% to 82% relative abundance of isolates belonging to C. cayetanensis. Overall, our analysis uncovers previously unknown temporal-genetic patterns in US Cyclospora types from 2018 through 2022 and is an important step to presenting a clearer picture of the factors influencing cyclosporiasis outbreaks in the USA.

An improved framework for detecting discrete epidemiologically meaningful partitions in hierarchically clustered genetic data

Motivation

Hierarchical clustering of microbial genotypes has the limitation that hierarchical clusters are nested, where smaller groups of related isolates exist within larger groups that get progressively larger as relationships become increasingly distant. In an epidemiologic context, investigators must dissect hierarchical trees into discrete groupings that are epidemiologically meaningful. We recently described a statistical framework (Method A) for dissecting hierarchical trees that attempts to minimize investigator bias. Here, we apply a modified version of that framework (Method B) to a hierarchical tree constructed from 2111 genotypes of the foodborne parasite Cyclospora, including 639 genotypes linked to epidemiologically defined outbreaks. To evaluate Method B's performance, we examined the concordance between these epidemiologically defined groupings and the genetic partitions identified. We also used the same epidemiologic clusters to evaluate the performance of Method A, plus two tree-dissection methods (cutreeHybrid and cutreeDynamic) available within the Dynamic Tree Cut R package, in addition to the TreeCluster method and PARNAS.

Results

Compared to the other methods, Method B, TreeCluster, and PARNAS were the most accurate (99.4%) in identifying genetic groups that reflected the epidemiologic groupings, noting that TreeCluster and PARNAS performed identically on our dataset. CutreeHybrid identified groups reflecting patterns in the wider Cyclospora population structure but lacked finer, strain-level discrimination (Simpson's D: cutreeHybrid=0.785). CutreeDynamic displayed good strain discrimination (Simpson's D = 0.933), though lacked sensitivity (77%). At two different threshold/radius settings TreeCluster/PARNAS displayed similar utility to Method B. However, Method B computes a tree-dissection threshold automatically, and the threshold/radius settings used when executing TreeCluster/PARNAS here were computed using Method B. Using a TreeCluster threshold of 0.045 as recommended in the TreeCluster documentation, epidemiologic utility dropped markedly below that of Method B.

Availability and implementation

Relevant code and data are publicly available. Source code (Method B) and instructions for its use are available here: https://github.com/Joel-Barratt/Hierarchical-tree-dissection-framework.

Cyclospora cayetanensis: A Perspective (2020-2023) with Emphasis on Epidemiology and Detection Methods

Cyclospora cayetanensis infections are prevalent worldwide, and the parasite has become a major public health and food safety concern. Although important efforts have been dedicated to advance toward preventing and reducing incidences of cyclosporiasis, there are still several knowledge gaps that hamper the implementation of effective measures to prevent the contamination of produce and water with Cyclospora oocysts. Some of these data gaps can be attributed to the fact that access to oocysts is a limiting factor in C. cayetanensis research. There are no animal models or in vivo or in vitro culture systems to propagate the oocysts needed to facilitate C. cayetanensis research. Thus, researchers must rely upon limited supplies of oocysts obtained from naturally infected human patients considerably restricting what can be learnt about this parasite. Despite the limited supply of C. cayetanensis oocysts, several important advances have happened in the past 3 years. Great progress has been made in the Cyclospora field in the areas of molecular characterization of strains and species, generation of genomes, and development of novel detection methods. This comprehensive perspective summarizes research published from 2020 to 2023 and evaluates what we have learnt and identifies those aspects in which further research is needed.

Retrospective evaluation of an integrated molecular-epidemiological approach to cyclosporiasis outbreak investigations - United States, 2021

Cyclosporiasis results from an infection of the small intestine by Cyclospora parasites after ingestion of contaminated food or water, often leading to gastrointestinal distress. Recent developments in temporally linking genetically related Cyclospora isolates demonstrated effectiveness in supporting epidemiological investigations. We used 'temporal-genetic clusters' (TGCs) to investigate reported cyclosporiasis cases in the United States during the 2021 peak-period (1 May - 31 August 2021). Our approach split 655 genotyped isolates into 55 genetic clusters and 31 TGCs. We linked two large multi-state epidemiological clusters (Epidemiologic Cluster 1 [n = 136 cases, 54 genotyped] and Epidemiologic Cluster 2 [n = 42 cases, 15 genotyped]) to consumption of lettuce varieties; however, product traceback did not identify a specific product for either cluster due to the lack of detailed product information. To evaluate the utility of TGCs, we performed a retrospective case study comparing investigation outcomes of outbreaks first detected using epidemiological methods with those of the same outbreaks had TGCs been used to first detect them. Our study results indicate that adjustments to routine epidemiological approaches could link additional cases to epidemiological clusters of cyclosporiasis. Overall, we show that CDC's integrated genotyping and epidemiological investigations provide valuable insights into cyclosporiasis outbreaks in the United States.

Development of a targeted amplicon sequencing method for genotyping Cyclospora cayetanensis from fresh produce and clinical samples with enhanced genomic resolution and sensitivity

Outbreaks of cyclosporiasis, an enteric illness caused by the parasite Cyclospora cayetanensis, have been associated with consumption of various types of fresh produce. Although a method is in use for genotyping C. cayetanensis from clinical specimens, the very low abundance of C. cayetanensis in food and environmental samples presents a greater challenge. To complement epidemiological investigations, a molecular surveillance tool is needed for use in genetic linkage of food vehicles to cyclosporiasis illnesses, estimation of the scope of outbreaks or clusters of illness, and determination of geographical areas involved. We developed a targeted amplicon sequencing (TAS) assay that incorporates a further enrichment step to gain the requisite sensitivity for genotyping C. cayetanensis contaminating fresh produce samples. The TAS assay targets 52 loci, 49 of which are located in the nuclear genome, and encompasses 396 currently known SNP sites. The performance of the TAS assay was evaluated using lettuce, basil, cilantro, salad mix, and blackberries inoculated with C. cayetanensis oocysts. A minimum of 24 markers were haplotyped even at low contamination levels of 10 oocysts in 25 g leafy greens. The artificially contaminated fresh produce samples were included in a genetic distance analysis based on haplotype presence/absence with publicly available C. cayetanensis whole genome sequence assemblies. Oocysts from two different sources were used for inoculation, and samples receiving the same oocyst preparation clustered together, but separately from the other group, demonstrating the utility of the assay for genetically linking samples. Clinical fecal samples with low parasite loads were also successfully genotyped. This work represents a significant advance in the ability to genotype C. cayetanensis contaminating fresh produce along with greatly expanding the genomic diversity included for genetic clustering of clinical specimens.

Cyclospora cayetanensis comprises at least 3 species that cause human cyclosporiasis

The apicomplexan parasite Cyclospora cayetanensis causes seasonal foodborne outbreaks of the gastrointestinal illness cyclosporiasis. Prior to the coronavirus disease-2019 pandemic, annually reported cases were increasing in the USA, leading the US Centers for Disease Control and Prevention to develop a genotyping tool to complement cyclosporiasis outbreak investigations. Thousands of US isolates and 1 from China (strain CHN_HEN01) were genotyped by Illumina amplicon sequencing, revealing 2 lineages (A and B). The allelic composition of isolates was examined at each locus. Two nuclear loci (CDS3 and 360i2) distinguished lineages A and B. CDS3 had 2 major alleles: 1 almost exclusive to lineage A and the other to lineage B. Six 360i2 alleles were observed – 2 exclusive to lineage A (alleles A1 and A2), 2 to lineage B (B1 and B2) and 1 (B4) was exclusive to CHN_HEN01 which shared allele B3 with lineage B. Examination of heterozygous genotypes revealed that mixtures of A- and B-type 360i2 alleles occurred rarely, suggesting a lack of gene flow between lineages. Phylogenetic analysis of loci from whole-genome shotgun sequences, mitochondrial and apicoplast genomes, revealed that CHN_HEN01 represents a distinct lineage (C). Retrospective examination of epidemiologic data revealed associations between lineage and the geographical distribution of US infections plus strong temporal associations. Given the multiple lines of evidence for speciation within human-infecting Cyclospora, we provide an updated taxonomic description of C. cayetanensis, and describe 2 novel species as aetiological agents of human cyclosporiasis: Cyclospora ashfordi sp. nov. and Cyclospora henanensis sp. nov. (Apicomplexa: Eimeriidae).

Optimizing hierarchical tree dissection parameters using historic epidemiologic data as 'ground truth'

Hierarchical clustering of pathogen genotypes is widely used to complement epidemiologic investigations of outbreaks. Investigators must dissect trees to obtain genetic partitions that provide epidemiologists with meaningful information. Statistical approaches to tree dissection often require a user-defined parameter to predict the optimal partition number and augmenting this parameter can drastically impact resultant partition memberships. Here, we demonstrate how to optimize a given tree dissection parameter to maximize accuracy irrespective of the tree dissection method used. We hierarchically clustered 1,873 genotypes of the foodborne pathogen Cyclospora spp., including 587 possessing links to historic outbreaks. We dissected the resulting tree using a statistical method requiring users to select the value of a 'stringency parameter' (s), with a recommended value of 95% to 99.5%. We dissected this hierarchical tree across s-values from 94% to 99.5% (at increments of 0.25%), to identify a value that maximized partitioning accuracy, defined as the degree to which genetic partitions conform to known epidemiologic groupings. We show that s-values of 96.5% and 96.75% yield the highest accuracy (> 99.9%) when clustering Cyclospora sp. isolates with known epidemiologic linkages. In practice, the optimized s-value will generate robust genetic partitions comprising isolates likely derived from a common food source, even when the epidemiologic grouping is not known prior to genetic clustering. While the s-value is specific to the tree dissection method used here, the optimization approach described could be applied to any parameter/method used to dissect hierarchical trees.

Genetic characterization of Strongyloides fuelleborni infecting free-roaming African vervets (Chlorocebus aethiops sabaeus) on the Caribbean island of St. Kitts

Human strongyloidiasis is an important neglected tropical disease primarily caused by the nematode Strongyloides stercoralis, and to a lesser extent Strongyloides fuelleborni which mainly infects non-human primates. Zoonotic sources of infection have important implications for control and prevention of morbidity and mortality caused by strongyloidiasis. Recent molecular evidence suggests that for S. fuelleborni, primate host specificity is variable among genotypes across the Old World, and consequently that these types likely vary in their capacity for human spillover infections. Populations of free-roaming vervet monkeys (Chlorocebus aethiops sabaeus), introduced to the Caribbean Island of Staint Kitts from Africa, live in close contact with humans, and concern has arisen regarding their potential to serve as reservoirs of zoonotic infections. In this study, we sought to determine the genotypes of S. fuelleborni infecting St. Kitts vervets to explore whether they are potential reservoirs for human-infecting S. fuelleborni types. Fecal specimens were collected from St. Kitts vervets and S. fuelleborni infections were confirmed microscopically and by PCR. Strongyloides fuelleborni genotypes were determined from positive fecal specimens using an Illumina amplicon sequencing-based genotyping approach targeting the mitochondrial cox1 locus and 18S rDNA hypervariable regions I and IV of Strongyloides species. Phylogenetic analysis of resultant genotypes supported that S. fuelleborni from St. Kitts vervets is of an exclusively African variety, falling within the same monophyletic group as an isolate which has been detected previously in a naturally infected human from Guinea-Bissau. This observation highlights that St. Kitts vervets may serve as potential reservoirs for zoonotic S. fuelleborni infection, which warrants further exploration.

Review on Cyclosporiasis Outbreaks and Potential Molecular Markers for Tracing Back Investigations

Cyclosporiasis is an emerging disease caused by Cyclospora cayetanensis, which induces protracting and relapsing gastroenteritis and has been linked to huge and complicated travel- and food-related outbreaks worldwide. Cyclosporiasis has become more common in both developing and developed countries as a result of increased global travel and the globalization of the human food supply. It is not just a burden on individual human health but also a worldwide public health problem. As a pathogen of interest, the molecular biological characteristics of C. cayetanensis have advanced significantly over the last few decades. However, only one FDA-approved molecular platform has been commercially used in the investigation of cyclosporiasis outbreaks. More potential molecular markers and genotyping of C. cayetanensis in samples based on the polymorphic region of the whole genomes might differentiate between separate case clusters and would be useful in tracing back investigations, especially during cyclosporiasis outbreak investigations. Considering that there is no effective vaccine for cyclosporosis, epidemiological investigation using effective tools is crucial for controlling cyclosporiasis by source tracking. Therefore, more and more epidemiological investigative studies for human cyclosporiasis should be promoted around the world to get a deeper understanding of its characteristics as well as management. This review focuses on major cyclosporiasis outbreaks and potential molecular markers for tracing back investigations into cyclosporiasis outbreaks.

Hastening Progress in Cyclospora Requires Studying Eimeria Surrogates

Cyclospora cayetanensis is an enigmatic human parasite that sickens thousands of people worldwide. The scarcity of research material and lack of any animal model or cell culture system slows research, denying the produce industry, epidemiologists, and regulatory agencies of tools that might aid diagnosis, risk assessment, and risk abatement. Fortunately, related species offer a strong foundation when used as surrogates to study parasites of this type. Species of Eimeria lend themselves especially well as surrogates for C. cayetanensis. Those Eimeria that infect poultry can be produced in abundance, share many biological features with Cyclospora, pose no risk to the health of researchers, and can be studied in their natural hosts. Here, we overview the actual and potential uses of such surrogates to advance understanding of C. cayetanensis biology, diagnostics, control, and genomics, focusing on opportunities to improve prevention, surveillance, risk assessment, and risk reduction. Studying Eimeria surrogates accelerates progress, closing important research gaps and refining promising tools for producers and food safety regulators to monitor and ameliorate the food safety risks imposed by this emerging, enigmatic parasite.

Development of a Molecular Marker Based on the Mitochondrial Genome for Detection of Cyclospora cayetanensis in Food and Water Samples

Cyclospora cayetanensis is a coccidian parasite that causes diarrheal illness outbreaks worldwide. The development of new laboratory methods for detection of C. cayetanensis is of critical importance because of the high potential for environmental samples to be contaminated with a myriad of microorganisms, adversely impacting the specificity when testing samples from various sources using a single molecular assay. In this study, a new sequencing-based method was designed targeting a specific fragment of C. cayetanensis cytochrome oxidase gene and developed as a complementary method to the TaqMan qPCR present in the U.S. FDA BAM Chapter 19b and Chapter 19c. The comparative results between the new PCR protocol and the qPCR for detection of C. cayetanensis in food and water samples provided similar results in both matrices with the same seeding level. The target region and primers in the protocol discussed in this study contain sufficient Cyclospora-specific sequence fidelity as observed by sequence comparison with other Eimeriidae species. The sequence of the PCR product appears to represent a robust target for identifying C. cayetanensis on samples from different sources. Such a sensitive method for detection of C. cayetanensis would add to the target repertoire of qPCR-based screening strategies for food and water samples.

Evaluation of various distance computation methods for construction of haplotype-based phylogenies from large MLST dataset

Multi-locus sequence typing (MLST) is widely used to investigate genetic relationships among eukaryotic taxa, including parasitic pathogens. MLST analysis workflows typically involve construction of alignment-based phylogenetic trees - i.e., where tree structures are computed from nucleotide differences observed in a multiple sequence alignment (MSA). Notably, alignment-based phylogenetic methods require that all isolates/taxa are represented by a single sequence. When multiple loci are sequenced these sequences may be concatenated to produce one tree that includes information from all loci. Alignment-based phylogenetic techniques are robust and widely used yet possess some shortcomings, including how heterozygous sites are handled, intolerance for missing data (i.e., partial genotypes), and differences in the way insertions-deletions (indels) are scored/treated during tree construction. In certain contexts, 'haplotype-based' methods may represent a viable alternative to alignment-based techniques, as they do not possess the aforementioned limitations. This is namely because haplotype-based methods assess genetic similarity based on numbers of shared (i.e., intersecting) haplotypes as opposed to similarities in nucleotide composition observed in an MSA. For haplotype-based comparisons, choosing an appropriate distance statistic is fundamental, and several statistics are available to choose from. However, a comprehensive assessment of various available statistics for their ability to produce a robust haplotype-based phylogenetic reconstruction has not yet been performed. We evaluated seven distance statistics by applying them to extant MLST datasets from the gastrointestinal parasite Cyclospora cayetanensis and two species of pathogenic nematode of the genus Strongyloides. We compare the genetic relationships identified using each statistic to epidemiologic, geographic, and host metadata. We show that Barratt's heuristic definition of genetic distance was the most robust among the statistics evaluated. Consequently, it is proposed that Barratt's heuristic represents a useful approach for use in the context of challenging MLST datasets possessing features (i.e., high heterozygosity, partial genotypes, and indel or repeat-based polymorphisms) that confound or preclude the use of alignment-based methods.

Genotyping Canadian Cyclospora cayetanensis Isolates to Supplement Cyclosporiasis Outbreak Investigations

Cyclospora cayetanensis is an emerging foodborne parasite that causes cyclosporiasis, an enteric disease of humans. Domestically acquired outbreaks have been reported in Canada every spring or summer since 2013. To date, investigations into the potential sources of infection have relied solely on epidemiological data. To supplement the epidemiological data with genetic information, we genotyped 169 Canadian cyclosporiasis cases from stool specimens collected from 2010 to 2021 using an existing eight-marker targeted amplicon deep (TADS) scheme specific to C. cayetanensis as previously described by the US Centers for Disease Control and Prevention (CDC). This is the first study to genotype Canadian Cyclospora cayetanensis isolates, and it focuses on evaluating the genotyping performance and genetic clustering. Genotyping information was successfully collected with at least part of one of the markers in the TADS assay for 97.9% of specimens, and 81.1% of cyclosporiasis cases met the minimum requirements to genetically cluster into 20 groups. The performance of the scheme suggests that examining cyclosporiasis cases genetically will be a valuable tool for supplementing epidemiological outbreak investigations and to minimize further infections. Further research is required to expand the number of discriminatory markers to improve genetic clustering.

Strongyloides genotyping: a review of methods and application in public health and population genetics

Strongyloidiasis represents a major medical and veterinary helminthic disease. Human infection is caused by Strongyloides stercoralis, Strongyloides fuelleborni fuelleborni and Strongyloides fuelleborni kellyi, with S.stercoralis accounting for the majority of cases. Strongyloides f. fuelleborni likely represents a zoonosis acquired from non-human primates (NHPs), while no animal reservoir for S. f. kellyi infection has been found. Whether S. stercoralis represents a zoonosis acquired from dogs and cats remains unanswered. Over the past two decades various tools have been applied to genotype Strongyloides spp. The most commonly sequenced markers have been the hyper-variable regions I and IV of the 18S rRNA gene and selected portions of the cytochrome c oxidase subunit I gene. These markers have been sequenced and compared in Strongyloides from multiple hosts and geographical regions. More recently, a machine learning algorithm multi-locus sequence typing approach has been applied using these markers, while others have applied whole genome sequencing. Genotyping of Strongyloides from dogs, cats, NHPs and humans has identified that S. stercoralis likely originated in dogs and adapted to human hosts. It has also been demonstrated that S. stercoralis is distinct from S. f. fuelleborni and S. f. kellyi. Two distinct genetic clades of S. stercoralis exist, one restricted to dogs and another infecting humans, NHPs, dogs and cats. Genotyping of S. f. fuelleborni has identified two separate clades, one associated with African isolates and another Indochinese peninsular clade. This review summarises the history and development of genotyping tools for Strongyloides spp. It describes the findings of major studies to date in the context of the epidemiology and evolutionary biology of these helminths, with a specific focus on human-infecting species.

Genotyping Cyclospora cayetanensis from multiple outbreak clusters with an emphasis on a cluster linked to bagged salad mix - United States, 2020

Cyclosporiasis is a diarrheal illness caused by the foodborne parasite Cyclospora cayetanensis. Annually reported cases have been increasing in the United States prompting development of genotyping tools to aid cluster detection. A recently developed Cyclospora genotyping system based on 8 genetic markers was applied to clinical samples collected during the cyclosporiasis peak period of 2020, facilitating assessment of its epidemiologic utility. While the system performed well and helped inform epidemiologic investigations, inclusion of additional markers to improve cluster detection was supported. Consequently, investigations have commenced to identify additional markers to enhance performance.

Dynamically expressed genes provide candidate viability biomarkers in a model coccidian

Eimeria parasites cause enteric disease in livestock and the closely related Cyclosporacayetanensis causes human disease. Oocysts of these coccidian parasites undergo maturation (sporulation) before becoming infectious. Here, we assessed transcription in maturing oocysts of Eimeria acervulina, a widespread chicken parasite, predicted gene functions, and determined which of these genes also occur in C. cayetanensis. RNA-Sequencing yielded ~2 billion paired-end reads, 92% of which mapped to the E. acervulina genome. The ~6,900 annotated genes underwent temporally-coordinated patterns of gene expression. Fifty-three genes each contributed >1,000 transcripts per million (TPM) throughout the study interval, including cation-transporting ATPases, an oocyst wall protein, a palmitoyltransferase, membrane proteins, and hypothetical proteins. These genes were enriched for 285 gene ontology (GO) terms and 13 genes were ascribed to 17 KEGG pathways, defining housekeeping processes and functions important throughout sporulation. Expression differed in mature and immature oocysts for 40% (2,928) of all genes; of these, nearly two-thirds (1,843) increased their expression over time. Eight genes expressed most in immature oocysts, encoding proteins promoting oocyst maturation and development, were assigned to 37 GO terms and 5 KEGG pathways. Fifty-six genes underwent significant upregulation in mature oocysts, each contributing at least 1,000 TPM. Of these, 40 were annotated by 215 GO assignments and 9 were associated with 18 KEGG pathways, encoding products involved in respiration, carbon fixation, energy utilization, invasion, motility, and stress and detoxification responses. Sporulation orchestrates coordinated changes in the expression of many genes, most especially those governing metabolic activity. Establishing the long-term fate of these transcripts in sporulated oocysts and in senescent and deceased oocysts will further elucidate the biology of coccidian development, and may provide tools to assay infectiousness of parasite cohorts. Moreover, because many of these genes have homologues in C. cayetanensis, they may prove useful as biomarkers for risk.

Investigation of US Cyclospora cayetanensis outbreaks in 2019 and evaluation of an improved Cyclospora genotyping system against 2019 cyclosporiasis outbreak clusters

Cyclosporiasis is an illness characterised by watery diarrhoea caused by the food-borne parasite Cyclospora cayetanensis. The increase in annual US cyclosporiasis cases led public health agencies to develop genotyping tools that aid outbreak investigations. A team at the Centers for Disease Control and Prevention (CDC) developed a system based on deep amplicon sequencing and machine learning, for detecting genetically-related clusters of cyclosporiasis to aid epidemiologic investigations. An evaluation of this system during 2018 supported its robustness, indicating that it possessed sufficient utility to warrant further evaluation. However, the earliest version of CDC's system had some limitations from a bioinformatics standpoint. Namely, reliance on proprietary software, the inability to detect novel haplotypes and absence of a strategy to select an appropriate number of discrete genetic clusters would limit the system's future deployment potential. We recently introduced several improvements that address these limitations and the aim of this study was to reassess the system's performance to ensure that the changes introduced had no observable negative impacts. Comparison of epidemiologically-defined cyclosporiasis clusters from 2019 to analogous genetic clusters detected using CDC's improved system reaffirmed its excellent sensitivity (90%) and specificity (99%), and confirmed its high discriminatory power. This C. cayetanensis genotyping system is robust and with ongoing improvement will form the basis of a US-wide C. cayetanensis genotyping network for clinical specimens.

Cyclosporiasis-Updates on Clinical Presentation, Pathology, Clinical Diagnosis, and Treatment

Cyclospora cayetanensis is an intestinal coccidian parasite transmitted to humans through the consumption of oocysts in fecally contaminated food and water. Infection is found worldwide and is highly endemic in tropical and subtropical regions with poor sanitation. Disease in developed countries is usually observed in travelers and in seasonal outbreaks associated with imported produce from endemic areas. Recently, summertime outbreaks in the United States have also been linked to locally grown produce. Cyclosporiasis causes a diarrheal illness which may be severe in infants, the elderly, and immunocompromised individuals. The increased adoption of highly sensitive molecular diagnostic tests, including commercially available multiplex panels for gastrointestinal pathogens, has facilitated the detection of infection and likely contributed to the increased reports of cases in developed countries. This manuscript reviews important aspects of the biology, epidemiology, and clinical manifestations of C. cayetanensis and provides an in-depth discussion of current laboratory diagnostic methods.

Identification of a Cyclospora cayetanensis Oocyst Antigens and Their Validity in the Detection of Immunogenic Patterns of Cyclosporiasis Patients

INTRODUCTION

The diagnosis of cyclosporiasis is currently based on the microscopic detection of oocysts, which may provide invalid results. The availability of simple, objective immunological screening tests would facilitate epidemiological studies of cyclosporiasis. Therefore, the present study aimed to identify the antigens of Cyclospora cayetanensis oocysts and their validity in serodiagnosis.

METHODS

According to parasitological and molecular diagnoses, three study groups were specified. Group (G) I included 30 patients with cyclosporiasis, GII included 12 patients with other parasitic infections, and GIII included 16 healthy subjects. SDS-PAGE was used to analyse C. cayetanensis antigens, and the validity of western blotting and enzyme-linked immunosorbent assays (ELISAs) was then assessed amongst the sera of all study groups.

RESULTS

The C. cayetanensis antigenic profile showed eight characteristic bands with molecular weights ranging from 14 to 175 kDa. Western blot analysis of sera revealed 93.3% (28/30 of GI) and 92.8% (26/28 of GII and III) sensitivity and specificity, respectively, dividing the patients in GI into four subgroups. The most frequent diagnostic bands (71.4% of GI sera) showed weights of 26-28 kDa, followed by 71 kDa (53.6%). ELISA sensitivity was 90% (27/30), and specificity was 78.6%. Validation showed perfect agreement between the PCR and western blot results, and ELISA presented substantial agreement with both the PCR and western blot results.

CONCLUSIONS

Our findings suggest the existence of high immunogenic diversity in C. cayetanensis and indicate that the 26-28 kDa immunogenic groups may potentially be used as a diagnostic marker of cyclosporiasis. Due to the high validity of ELISA, it might be the test of choice for the routine serodiagnosis of cyclosporiasis.

Nonparametric Binary Classification to Distinguish Closely Related versus Unrelated Plasmodium falciparum Parasites

Assessing genetic relatedness of Plasmodium falciparum genotypes is a key component of antimalarial efficacy trials. Previous methods have focused on determining a priori definitions of the level of genetic similarity sufficient to classify two infections as sharing the same strain. However, factors such as mixed-strain infections, allelic suppression, imprecise typing methods, and heterozygosity complicate comparisons of apicomplexan genotypes. Here, we introduce a novel method for nonparametric statistical testing of relatedness for P. falciparum parasites. First, the background distribution of genetic distance between unrelated strains is computed. Second, a threshold genetic distance is computed from this empiric distribution of distances to demarcate genetic distances that are unlikely to have arisen by chance. Third, the genetic distance between paired samples is computed, and paired samples with genetic distances below the threshold are classified as related. The method is designed to work with any arbitrary genetic distance definition. We validated this procedure using two independent approaches to calculating genetic distance. We assessed the concordance of the novel nonparametric classification with a gold-standard Bayesian approach for 175 pairs of recurrent P. falciparum episodes from previously published malaria efficacy trials with microsatellite data from five studies in Guinea and Angola. The novel nonparametric approach was 98% sensitive and 84-89% specific in correctly identifying related genotypes compared with a gold-standard Bayesian algorithm. The approach provides a unified and systematic method to statistically assess relatedness of P. falciparum parasites using arbitrary genetic distance methodologies.

Machine learning and applications in microbiology

To understand the intricacies of microorganisms at the molecular level requires making sense of copious volumes of data such that it may now be humanly impossible to detect insightful data patterns without an artificial intelligence application called machine learning. Applying machine learning to address biological problems is expected to grow at an unprecedented rate, yet it is perceived by the uninitiated as a mysterious and daunting entity entrusted to the domain of mathematicians and computer scientists. The aim of this review is to identify key points required to start the journey of becoming an effective machine learning practitioner. These key points are further reinforced with an evaluation of how machine learning has been applied so far in a broad scope of real-life microbiology examples. This includes predicting drug targets or vaccine candidates, diagnosing microorganisms causing infectious diseases, classifying drug resistance against antimicrobial medicines, predicting disease outbreaks and exploring microbial interactions. Our hope is to inspire microbiologists and other related researchers to join the emerging machine learning revolution.

Host Range of Cyclospora Species: Zoonotic Implication

Cyclospora is an intracellular, gastrointestinal parasite found in birds and mammals worldwide. Limited accessibility of the protozoan for experimental use, scarcity, genome heterogeneity of the isolates and narrow panel of molecular markers hamper zoonotic investigations. One of the significant limitation in zoonotic studies is the lack of precise molecular tools that would be useful in linking animal vectors as a source of human infection. Strong and convincing evidence of zoonotic features will be achieved through proper typing of Cyclospora spp. taxonomic units (e.g. species or genotypes) in animal reservoirs. The most promising method that can be employ for zoonotic surveys is next-generation sequencing.

Machine learning-based analyses support the existence of species complexes for Strongyloides fuelleborni and Strongyloides stercoralis

Human strongyloidiasis is a serious disease mostly attributable to Strongyloides stercoralis and to a lesser extent Strongyloides fuelleborni, a parasite mainly of non-human primates. The role of animals as reservoirs of human-infecting Strongyloides is ill-defined, and whether dogs are a source of human infection is debated. Published multi-locus sequence typing (MLST) studies attempt to elucidate relationships between Strongyloides genotypes, hosts, and distributions, but typically examine relatively few worms, making it difficult to identify population-level trends. Combining MLST data from multiple studies is often impractical because they examine different combinations of loci, eliminating phylogeny as a means of examining these data collectively unless hundreds of specimens are excluded. A recently-described machine learning approach that facilitates clustering of MLST data may offer a solution, even for datasets that include specimens sequenced at different combinations of loci. By clustering various MLST datasets as one using this procedure, we sought to uncover associations among genotype, geography, and hosts that remained elusive when examining datasets individually. Multiple datasets comprising hundreds of S. stercoralis and S. fuelleborni individuals were combined and clustered. Our results suggest that the commonly proposed 'two lineage' population structure of S. stercoralis (where lineage A infects humans and dogs, lineage B only dogs) is an over-simplification. Instead, S. stercoralis seemingly represents a species complex, including two distinct populations over-represented in dogs, and other populations vastly more common in humans. A distinction between African and Asian S. fuelleborni is also supported here, emphasizing the need for further resolving these taxonomic relationships through modern investigations.

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.

Development of a workflow for identification of nuclear genotyping markers for Cyclospora cayetanensis

Cyclospora cayetanensis is an intestinal parasite responsible for the diarrheal illness, cyclosporiasis. Molecular genotyping, using targeted amplicon sequencing, provides a complementary tool for outbreak investigations, especially when epidemiological data are insufficient for linking cases and identifying clusters. The goal of this study was to identify candidate genotyping markers using a novel workflow for detection of segregating single nucleotide polymorphisms (SNPs) in C. cayetanensis genomes. Four whole C. cayetanensis genomes were compared using this workflow and four candidate markers were selected for evaluation of their genotyping utility by PCR and Sanger sequencing. These four markers covered 13 SNPs and resolved parasites from 57 stool specimens, differentiating C. cayetanensis into 19 new unique genotypes.

Molecular typing of Cyclospora cayetanensis in produce and clinical samples using targeted enrichment of complete mitochondrial genomes and next-generation sequencing

BACKGROUND

Outbreaks of cyclosporiasis, a diarrheal illness caused by Cyclospora cayetanensis, have been a public health issue in the USA since the mid 1990's. In 2018, 2299 domestically acquired cases of cyclosporiasis were reported in the USA as a result of multiple large outbreaks linked to different fresh produce commodities. Outbreak investigations are hindered by the absence of standardized molecular epidemiological tools for C. cayetanensis. For other apicomplexan coccidian parasites, multicopy organellar DNA such as mitochondrial genomes have been used for detection and molecular typing.

METHODS

We developed a workflow to obtain complete mitochondrial genome sequences from cilantro samples and clinical samples for typing of C. cayetanensis isolates. The 6.3 kb long C. cayetanensis mitochondrial genome was amplified by PCR in four overlapping amplicons from genomic DNA extracted from cilantro, seeded with oocysts, and from stool samples positive for C. cayetanensis by diagnostic methods. DNA sequence libraries of pooled amplicons were prepared and sequenced via next-generation sequencing (NGS). Sequence reads were assembled using a custom bioinformatics pipeline.

RESULTS

This approach allowed us to sequence complete mitochondrial genomes from the samples studied. Sequence alterations, such as single nucleotide polymorphism (SNP) profiles and insertion and deletions (InDels), in mitochondrial genomes of 24 stool samples from patients with cyclosporiasis diagnosed in 2014, exhibited discriminatory power. The cluster dendrogram that was created based on distance matrices of the complete mitochondrial genome sequences, indicated distinct strain-level diversity among the 2014 C. cayetanensis outbreak isolates analyzed in this study.

CONCLUSIONS

Our results suggest that genomic analyses of mitochondrial genome sequences may help to link outbreak cases to the source.

A Molecular Tool for Rapid Detection and Traceability of Cyclospora cayetanensis in Fresh Berries and Berry Farm Soils

Due to recent outbreaks of cyclosporiasis associated with consumption of fresh berries, producers are demanding modern microbiological tools for the rapid and accurate identification of the human pathogen Cyclospora cayetanensis in berries and environmental samples. The aim of the present work was to develop a molecular tool based on a PCR approach for the rapid and accurate detection of C. cayetanensis. A nested PCR assay was validated for the amplification of a 294 bp size region of the 18S rRNA gene from C. cayetanensis. The limit of detection for the nested PCR assay was validated using 48 berry samples spiked with ~0, 10, 100, and 1000 oocyst per gram of sample. With this assay, it was possible to detect as few as 1 oocyst per gram of berry, in a 50 g sample. Sanger DNA sequencing and phylogenetic analysis were carried out to confirm the presence of C. cayetanensis in berry (n = 17) and soil (n = 5) samples. The phylogenetic analysis revealed that the C. cayetanensis sequences obtained from Mexico clustered within a group recovered from China, Peru, Guatemala-Haiti, and Japan. The PCR protocol designed in the present study could be an important tool for the rapid and accurate detection of this human pathogen in environmental and food samples.

Advances in Cyclosporiasis Diagnosis and Therapeutic Intervention

Cyclosporiasis is caused by the coccidian parasite Cyclospora cayetanensis and is associated with large and complex food-borne outbreaks worldwide. Associated symptoms include severe watery diarrhea, particularly in infants, and immune dysfunction. With the globalization of human food supply, the occurrence of cyclosporiasis has been increasing in both food growing and importing countries. As well as being a burden on the health of individual humans, cyclosporiasis is a global public health concern. Currently, no vaccine is available but early detection and treatment could result in a favorable clinical outcome. Clinical diagnosis is based on cardinal clinical symptoms and conventional laboratory methods, which usually involve microscopic examination of wet smears, staining tests, fluorescence microscopy, serological testing, or DNA testing for oocysts in the stool. Detection in the vehicle of infection, which can be fresh produce, water, or soil is helpful for case-linkage and source-tracking during cyclosporiasis outbreaks. Treatment with trimethoprim-sulfamethoxazole (TMP-SMX) can evidently cure C. cayetanensis infection. However, TMP-SMX is not suitable for patients having sulfonamide intolerance. In such case ciprofloxacin, although less effective than TMP-SMX, is a good option. Another drug of choice is nitazoxanide that can be used in the cases of sulfonamide intolerance and ciprofloxacin resistance. More epidemiological research investigating cyclosporiasis in humans should be conducted worldwide, to achieve a better understanding of its characteristics in this regard. It is also necessary to establish in vitro and/or in vivo protocols for cultivating C. cayetanensis, to facilitate the development of rapid, convenient, precise, and economical detection methods for diagnosis, as well as more effective tracing methods. This review focuses on the advances in clinical features, diagnosis, and therapeutic intervention of cyclosporiasis.

Pathogen Genomics in Public Health

Rapid advances in DNA sequencing technology ("next-generation sequencing") have inspired optimism about the potential of human genomics for "precision medicine." Meanwhile, pathogen genomics is already delivering "precision public health" through more effective investigations of outbreaks of foodborne illnesses, better-targeted tuberculosis control, and more timely and granular influenza surveillance to inform the selection of vaccine strains. In this article, we describe how public health agencies have been adopting pathogen genomics to improve their effectiveness in almost all domains of infectious disease. This momentum is likely to continue, given the ongoing development in sequencing and sequencing-related technologies.

Cyclospora cayetanensis and Cyclosporiasis: An Update

Cyclospora cayetanensis is a coccidian parasite of humans, with a direct fecal-oral transmission cycle. It is globally distributed and an important cause of foodborne outbreaks of enteric disease in many developed countries, mostly associated with the consumption of contaminated fresh produce. Because oocysts are excreted unsporulated and need to sporulate in the environment, direct person-to-person transmission is unlikely. Infection by C. cayetanensis is remarkably seasonal worldwide, although it varies by geographical regions. Most susceptible populations are children, foreigners, and immunocompromised patients in endemic countries, while in industrialized countries, C. cayetanensis affects people of any age. The risk of infection in developed countries is associated with travel to endemic areas and the domestic consumption of contaminated food, mainly fresh produce imported from endemic regions. Water and soil contaminated with fecal matter may act as a vehicle of transmission for C. cayetanensis infection. The disease is self-limiting in most immunocompetent patients, but it may present as a severe, protracted or chronic diarrhea in some cases, and may colonize extra-intestinal organs in immunocompromised patients. Trimetoprim-sulfamethoxazole is the antibiotic of choice for the treatment of cyclosporiasis, but relapses may occur. Further research is needed to understand many unknown epidemiological aspects of this parasitic disease. Here, we summarize the biology, epidemiology, outbreaks, clinical symptoms, diagnosis, treatment, control and prevention of C. cayetanensis; additionally, we outline future research needs for this parasite.