The first Cyclospora cayetanensis lineage A genome from an isolate from Mexico.

BACKGROUND: Cyclospora cayetanensis is a protozoan parasite that causes intestinal illness in humans worldwide. Despite its global distribution, most genomic data for C. cayetanensis has been obtained from isolates collected in the United States, leaving genetic variability among globally distributed isolates underexplored. RESULTS: In the present study, the genome of an isolate of C. cayetanensis obtained from a child with diarrhea living in Mexico was sequenced and assembled. Evaluation of the assembly using a lineage typing system recently developed by the Centers for Disease Control and Prevention revealed that this isolate is lineage A. CONCLUSIONS: Given that the only other whole genome assembly available from Mexico was classified as lineage B, the data presented here represent an important step in expanding our knowledge of the diversity of C. cayetanensis isolates from Mexico at the genomic level.

Epidemiologic Utility of a Framework for Partition Number Selection When Dissecting Hierarchically Clustered Genetic Data Evaluated on the Intestinal Parasite Cyclospora cayetanensis.

Comparing parasite genotypes to inform parasitic disease outbreak investigations involves computation of genetic distances that are typically analyzed by hierarchical clustering to identify related isolates, indicating a common source. A limitation of hierarchical clustering is that hierarchical clusters are not discrete; they are nested. Consequently, small groups of similar isolates exist within larger groups that get progressively larger as relationships become increasingly distant. Investigators must dissect hierarchical trees at a partition number ensuring grouped isolates belong to the same strain; a process typically performed subjectively, introducing bias into resultant groupings. We describe an unbiased, probabilistic framework for partition number selection that ensures partitions comprise isolates that are statistically likely to belong to the same strain. We computed distances and established a normalized distribution of background distances that we used to demarcate a threshold below which the closeness of relationships is unlikely to be random. Distances are hierarchically clustered and the dendrogram dissected at a partition number where most within-partition distances fall below the threshold. We evaluated this framework by partitioning 1,137 clustered Cyclospora cayetanensis genotypes, including 552 isolates epidemiologically linked to various outbreaks. The framework was 91% sensitive and 100% specific in assigning epidemiologically linked isolates to the same partition.

First report on occurrence and genotypes of Enterocytozoon bieneusi, Cryptosporidium spp. and Cyclospora cayetanensis from diarrheal outpatients in Ningbo, Southeast China.

Enterocytozoon bieneusi, Cryptosporidium spp. and Cyclospora cayetanensis are three important zoonotic pathogens which were a major cause of foodborne or waterborne intestinal diseases in humans and animals. However, very little data about occurrence and genotypes of the three parasites in Ningbo in the south wing of the Yangtze River Delta, China, which is important for a tourist city. In the present study, molecular characterization of E. bieneusi, C. cayetanensis and Cryptosporidium spp. in fecal samples from 489 diarrheal outpatients were carried out. As a result, a total of 35 (7.16%, 35/489) and three (0.61%, 3/489) samples were positive for E. bieneusi and C. cayetanensis respectively. No Cryptosporidium-positive sample or mixed-infections were detected. Four known E. bieneusi genotypes (Type IV, D, I and CHN4) and 8 novel genotypes (NBH1-NBH8) were identified with type IV was the dominant genotype (n = 14), followed by genotypes D (n = 5), NBH8 (n = 5) and NBH7 (n = 3). The remaining genotypes were found in one sample each, and these genotypes were belonged to the previously described high-potential zoonotic group 1. One novel sequence named NBC315, and the other two sequences (NBC30 and NBC370) identical with the reported sequence were detected. Therefore, the existence and importance of zoonotic potential of E. bieneusi and C. cayetanensis in diarrheal outpatients in Ningbo indicates the public health threats, and more investigations should be carried out in human populations, animals and other environmental sources from the One Health perspective.

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.

Immunogenic multi-epitope-based vaccine development to combat cyclosporiasis of immunocompromised patients applying computational biology method.

Cyclospora cayetanensis infections, also known as cyclosporiasis, persist to be the prevalent emerging protozoan parasite and an opportunist that causes digestive illness in immunocompromised individuals. In contrast, this causal agent can affect people of all ages, with children and foreigners being the most susceptible populations. For most immunocompetent patients, the disease is self-limiting; in extreme circumstances, this illness can manifest as severe or persistent diarrhea as well as colonize on secondary digestive organs leading to death. According to recent reports, worldwide 3.55% of people are infected by this pathogen, with Asia and Africa being more prevalent. For the treatment, trimethoprim-sulfamethoxazole is the only licensed drug and does not appear to work as well in some patient populations. Therefore, the much more effective strategy to avoid this illness is immunization through the vaccine. This present study uses immunoinformatics for identifying a computational multi-epitope-based peptide vaccine candidate for Cyclospora cayetanensis. Following the review of the literature, a highly efficient, secure, and vaccine complex based on multi-epitopes was designed by utilizing the identified proteins. These selected proteins were then used to predict non-toxic and antigenic HTL-epitopes, B-cell-epitopes, and CTL-epitopes. Ultimately, both a few linkers and an adjuvant were combined to create a vaccine candidate with superior immunological epitopes. Then, to establish the vaccine-TLR complex binding constancy, the TLR receptor and vaccine candidates were placed into the FireDock, PatchDock, and ClusPro servers for molecular docking and iMODS server for molecular-dynamic simulation. Finally, this selected vaccine construct was cloned into Escherichia coli strain-K12; thus, the constructed vaccines against Cyclospora cayetanensiscould improve the host immune response and can be produced experimentally.

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.

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.

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

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.

Surveillance of berries sold on the Norwegian market for parasite contamination using molecular methods.

The risk of foodborne parasite infection linked to the consumption of contaminated fresh produce has long been known. However, despite epidemiological links between the outbreaks and contaminated berries, few studies have assessed the magnitude of parasite contamination on fresh produce sold in Europe. The present study was aimed to address the knowledge gap on parasite contamination of berries sold in Norway. Samples of blueberries, strawberries, and raspberries were analysed by multiplex qPCR for detection of Echinococcus multilocularis, Toxoplasma gondii, and Cyclospora cayetanensis. In addition, a simplex qPCR method was employed for detecting contamination of the berries with Cryptosporidium spp. A total of 820 samples of berries, each of around 30 g (274 samples of blueberries, 276 samples of raspberries, and 270 samples of strawberries), were analysed. We found an overall occurrence of 2.9%, 6.6%, and 8.3% for T. gondii, C. cayetanensis, and Cryptosporidium spp., respectively, whereas E. multilocularis was not detected from any of the samples investigated. Strawberries and raspberries were most often contaminated with Cryptosporidium spp., whereas blueberries were contaminated mostly with C. cayetanensis. Detection of parasite contaminants on fresh berries indicates the need for a system to ensure the parasitological safety of fresh berries.

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.

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.

Detection of Cyclospora cayetanensis on bagged pre-cut salad mixes within their shelf-life and after sell by date by the U.S. food and drug administration validated method.

Recently, outbreaks of Cyclospora cayetanensis in the U.S. were linked to the consumption of a variety of salads containing romaine and/or iceberg lettuce, carrots and/or red cabbage. The Bacteriological Analytical Manual (BAM) Chapter 19b method was validated for the detection of C. cayetanensis in carrots, cabbage and romaine lettuce, but has not been previously evaluated in ready-to-eat (RTE) salad mixes. In addition, the only samples available for traceback investigations are sometimes leftovers in bad conditions. This study evaluated the validated BAM method for detection of C. cayetanensis in two different RTE mixed salads (mix 1: romaine and iceberg lettuces, carrots, and red cabbage and mix 2: romaine and iceberg lettuces, carrots, red cabbage, radish, and pea pods) in good condition and after their sell by date. Individual samples (25 g) were seeded with five and 200 C. cayetanensis oocysts. Unseeded produce was used as negative control. The method included washing of the produce, concentration and extraction of C. cayetanensis DNA and molecular detection of C. cayetanensis 18 S rRNA gene. As few as five oocysts were detected in both fresh and after sell by date mix salads. All unseeded samples were negative, and all samples of both salad types seeded with 200 oocysts were positive. In samples seeded with 200 oocysts, average 18 S rRNA C. cayetanensis CT values were significantly higher in fresh salad mix 1 compared to fresh salad mix 2; CT values were significantly higher in the after sell by date salads compared to their respective fresh mixes (p < 0.05). In conclusion, the BAM method was able to detect as few as five oocysts even in after sell by date RTE mix salads. However, the differences in detection observed, highlight the importance of evaluating the performance of the validated C. cayetanensis detection method in different food matrices and conditions, in advance for future outbreak investigations.

Contamination of fresh produce sold on the Italian market with Cyclospora cayetanensis and Echinococcus multilocularis.

To investigate the presence of Cyclospora cayetanensis, Toxoplasma gondii and Echinococcus spp. in fresh produce sold in Italy, 324 locally produced 'ready-to-eat' (RTE) mixed-salad packages belonging to three brands and 324 berries packages (blueberries and blackberries imported from Peru and Mexico, respectively, and raspberries grown in Italy) were purchased at retail. Nine individual packages from each of the six types of fresh produce were collected monthly for one year, and with the same produce pooled, this resulted in a total of 72 pools for the whole year. Using microscopy (FLOTAC), a Cyclospora-like oocyst was detected in a blueberry sample and a taeniid egg was detected in a RTE-salad sample. Molecular tools confirmed these to be C. cayetanensis and Echinococcus multilocularis, respectively. Toxoplasma gondii was not detected in any of the samples. This study shows for the first time in Europe that imported berries on the Italian market may be contaminated with C. cayetanensis and RTE salads grown in Italy with E. multilocularis. The results indicate a new epidemiological scenario and highlight that current management of fresh produce, locally produced or imported, does not ensure products are free from parasite contamination.

Modifications of the U.S. food and drug administration validated method for detection of Cyclospora cayetanensis oocysts in prepared dishes: Mexican-style salsas and guacamole.

Although multiple outbreak clusters of Cyclospora cayetanensis have been traced back to consumption of dishes in Mexican-style restaurants, the FDA Bacteriological Analytical Manual (BAM) does not currently provide methods to detect C. cayetanensis in dishes that contain multiple produce ingredients, such as salsas and guacamole. These complex food matrices also may contain high levels of fats, which can interfere with the detection. Several modifications to the BAM Chapter 19b method (washing produce, DNA extraction, and a TaqMan real-time PCR assay targeting the 18S rRNA gene of C. cayetanensis) were assessed with the goal to detect as few as 5 oocysts of C. cayetanensis in 25 g samples of commercial salsa/pico de gallo, guacamole, and salsa verde. Both freshly prepared and frozen versions of these foods were seeded with 5, 10 and 200 oocysts. For salsa samples, using a gentler washing step than recommended by BAM, we achieved detection of 5 oocysts in the samples (81.8%, n = 11). Increasing the amount of Alconox® in the wash solution to 1%, rather than the 0.1% used in BAM, and adjusting the DNA extraction protocol to process large wash pellets, enabled detection of 5 oocysts in guacamole. To reach the desired level of detection in salsa verde, two types of modifications were necessary: gentler washing and DNA extraction modifications. The use of these same method modifications on previously frozen food samples, provided levels of detection similar to those achieved with fresh dishes. Our modifications enabled robust and reproducible detection of C. cayetanensis in multi-ingredient Mexican dishes, detecting as few as 5 oocysts in 25 g samples. Validating and deploying effective methods to detect C. cayetanensis in high risk fresh produce and prepared dishes are critically important for prevalence studies and outbreak investigations of this parasite.

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.

Cyclospora cayetanensis infection in humans: biological characteristics, clinical features, epidemiology, detection method and treatment.

Cyclospora cayetanensis, a coccidian parasite that causes protracted and relapsing gastroenteritis, has a short recorded history. At least 54 countries have documented C. cayetanensis infections and 13 of them have recorded cyclosporiasis outbreaks. Cyclospora cayetanensis infections are commonly reported in developing countries with low-socioeconomic levels or in endemic areas, although large outbreaks have also been documented in developed countries. The overall C. cayetanensis prevalence in humans worldwide is 3.55%. Among susceptible populations, the highest prevalence has been documented in immunocompetent individuals with diarrhea. Infections are markedly seasonal, occurring in the rainy season or summer. Cyclospora cayetanensis or Cyclospora-like organisms have also been detected in food, water, soil and some other animals. Detection methods based on oocyst morphology, staining and molecular testing have been developed. Treatment with trimethoprim-sulfamethoxazole (TMP-SMX) effectively cures C. cayetanensis infection, whereas ciprofloxacin is less effective than TMP-SMX, but is suitable for patients who cannot tolerate co-trimoxazole. Here, we review the biological characteristics, clinical features, epidemiology, detection methods and treatment of C. cayetanensis in humans, and assess some risk factors for infection with this pathogen.

Evaluation of the U.S. Food and Drug Administration validated molecular method for detection of Cyclospora cayetanensis oocysts on fresh and frozen berries.

Outbreaks and sporadic cases of Cyclospora cayetanensis have been linked to consumption of berries. The efficacy of the U.S. Food and Drug Administration (FDA) method for detection of C. cayetanensis was evaluated in fresh berries (blackberries, strawberries, blueberries and mixed berries) and in frozen mixed berries. The protocol included seeding with C. cayetanensis oocysts, produce washing, DNA extraction and a dual TaqMan assay. As few as five oocysts were detected in every type of fresh berry analyzed. All berry samples seeded with 200 oocysts were positive and all unseeded berry samples were negative. No significant differences were observed among any of the berry types analyzed in detection rates, CT values and estimated oocyst recovery percentages. Mixed berries were seeded and frozen for up to seven weeks. As few as five oocysts were also detected. No significant differences were observed in C. cayetanensis CT values between fresh and frozen mixed berries at any seeding level. In conclusion, the FDA BAM Chapter 19B method for the detection of Cyclospora was robust, consistent, and showed high sensitivity in all types of berries analyzed. Evaluation of the FDA detection method in berries will provide reliable laboratory support for surveillance programs and for outbreak investigations.

Outbreak of Cyclosporiasis in Korean Travelers Returning from Nepal.

Cyclospora cayetanensis is an apicomplexan protozoan and is one of the most common pathogens causing chronic diarrhea worldwide. Eight stool samples with diarrheal symptom out of 18 Korean residents who traveled to Nepal were obtained, and examined for 25 enteropathogens including 16 bacterial species, 5 viral species, and 4 protozoans in stool samples as causative agents of water-borne and food-borne disease. Only C. cayetanensis was detected by nested PCR, and 3 PCR-positive samples were sequenced to confirm species identification. However, the oocysts of C. cayetanensis in fecal samples could not be detected by direct microscopy of the stained sample. As far as we know, this is the first report of a group infection with C. cayetanensis from a traveler visiting Nepal, and the second report of a traveler's diarrhea by C. cayetanensis imported in Korea.

Mitochondrial Junction Region as Genotyping Marker for Cyclospora cayetanensis.

Cyclosporiasis is an infection caused by Cyclospora cayetanensis, which is acquired by consumption of contaminated fresh food or water. In the United States, cases of cyclosporiasis are often associated with foodborne outbreaks linked to imported fresh produce or travel to disease-endemic countries. Epidemiologic investigation has been the primary method for linking outbreak cases. A molecular typing marker that can identify genetically related samples would be helpful in tracking outbreaks. We evaluated the mitochondrial junction region as a potential genotyping marker. We tested stool samples from 134 laboratory-confirmed cases in the United States by using PCR and Sanger sequencing. All but 2 samples were successfully typed and divided into 14 sequence types. Typing results were identical among samples within each epidemiologically defined case cluster for 7 of 10 clusters. These findings suggest that this marker can distinguish between distinct case clusters and might be helpful during cyclosporiasis outbreak investigations.

Genotyping genetically heterogeneous Cyclospora cayetanensis infections to complement epidemiological case linkage.

Sexually reproducing pathogens such as Cyclospora cayetanensis often produce genetically heterogeneous infections where the number of unique sequence types detected at any given locus varies depending on which locus is sequenced. The genotypes assigned to these infections quickly become complex when additional loci are analysed. This genetic heterogeneity confounds the utility of traditional sequence-typing and phylogenetic approaches for aiding epidemiological trace-back, and requires new methods to address this complexity. Here, we describe an ensemble of two similarity-based classification algorithms, including a Bayesian and heuristic component that infer the relatedness of C. cayetanensis infections. The ensemble requires a set of haplotypes as input and assigns arbitrary distances to specimen pairs reflecting their most likely relationships. The approach was applied to data generated from a test cohort of 88 human fecal specimens containing C. cayetanensis, including 30 from patients whose infections were associated with epidemiologically defined outbreak clusters of cyclosporiasis. The ensemble assigned specimens to plausible clusters of genetically related infections despite their complex haplotype composition. These relationships were corroborated by a significant number of epidemiological linkages (P < 0.0001) suggesting the ensemble's utility for aiding epidemiological trace-back investigations of cyclosporiasis.