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.

Sources and Prevalence of Cyclospora cayetanensis in Southeastern U.S. Growing Environments.

Recent cyclosporiasis outbreaks associated with fresh produce grown in the United States highlight the need to better understand Cyclospora cayetanensis prevalence in U.S. agricultural environments. In this study, C. cayetanensis occurrence was assessed in municipal wastewater sludge, on-farm portable toilets, irrigation pond water, and spent packing house dump tank water in a Southeastern Georgia growing region over two years. Detection of the C. cayetanensis 18S rRNA qPCR gene target in pond samples was 0%, 28%, and 42% (N = 217) depending on the detection definition used, and ≤1% in dump tank samples (N = 46). However, no qPCR detections were confirmed by sequencing, suggesting false detection occurred due to cross-reactions. C. cayetanensis qPCR detections were confirmed in 9% of wastewater sludge samples (N = 76). The human-specific fecal markers HF183 and crAssphage were detected in 33% and 6% of pond samples, respectively, and 4% and 0% of dump tank samples, respectively. Despite community Cyclospora shedding and evidence of human fecal contamination in irrigation water, there was no correlation between C. cayetanensis and HF183 qPCR detections, further supporting that 18S gene target qPCR amplifications were due to cross-reactions. When evaluating C. cayetanensis qPCR environmental detection data, the impact of assay specificity and detection criteria should be considered. Moreover, additional sequence-based testing may be needed to appropriately interpret Cyclospora qPCR environmental data.

Genetic characterization and description of Leishmania (Leishmania) ellisi sp. nov.: a new human-infecting species from the USA.

In a 2018 report, an unusual case of cutaneous leishmaniasis was described in a 72-year-old female patient residing in Arizona, United States of America (USA). Preliminary analysis of the 18S rDNA and glyceraldehyde-3-phosphate dehydrogenase genes supported the conclusion that the Leishmania strain (strain 218-L139) isolated from this case was a novel species, though a complete taxonomic description was not provided. Identification of Leishmania at the species level is critical for clinical management and epidemiologic investigations so it is important that novel human-infecting species are characterized taxonomically and assigned a unique scientific name compliant with the ICZN code. Therefore, we sought to provide a complete taxonomic description of Leishmania strain 218-L139. Phylogenetic analysis of several nuclear loci and partial maxicircle genome sequences supported its position within the subgenus Leishmania and further clarified the distinctness of this new species. Morphological characterization of cultured promastigotes and amastigotes from the original case material is also provided. Thus, we conclude that Leishmania (Leishmania) ellisi is a new cause of autochthonous cutaneous leishmaniasis in the USA.

Simultaneous targeted amplicon deep sequencing and library preparation for a time and cost-effective universal parasite diagnostic sequencing approach.

We recently described a targeted amplicon deep sequencing (TADS) strategy that utilizes a nested PCR targeting the 18S rDNA gene of blood-borne parasites. The assay facilitates selective digestion of host DNA by targeting enzyme restriction sites present in vertebrates but absent in parasites. This enriching of parasite-derived amplicon drastically reduces the proportion of host-derived reads during sequencing and results in the sensitive detection of several clinically important blood parasites including Plasmodium spp., Babesia spp., kinetoplastids, and filarial nematodes. Despite these promising results, high costs and the laborious nature of metagenomics sequencing are prohibitive to the routine use of this assay in most laboratories. We describe and evaluate a new metagenomic approach that utilizes a set of primers modified from our original assay that incorporates Illumina barcodes and adapters during the PCR steps. This modification makes amplicons immediately compatible with sequencing on the Illumina MiSeq platform, removing the need for a separate library preparation, which is expensive and time-consuming. We compared this modified assay to our previous nested TADS assay in terms of preparation speed, limit of detection (LOD), and cost. Our modifications reduced assay turnaround times from 7 to 5 days. The cost decreased from approximately $40 per sample to $11 per sample. The modified assay displayed comparable performance in the detection and differentiation of human-infecting Plasmodium spp., Babesia spp., kinetoplastids, and filarial nematodes in clinical samples. The LOD of this modified approach was determined for malaria parasites and remained similar to that previously reported for our earlier assay (0.58 Plasmodium falciparum parasites/µL of blood). These modifications markedly reduced costs and turnaround times, making the assay more amenable to routine diagnostic applications.

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.

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.

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.

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.

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.

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.

Application of a universal parasite diagnostic test to biological specimens collected from animals.

A previously described universal parasite diagnostic (nUPDx) based on PCR amplification of the 18S rDNA and deep-amplicon sequencing, can detect human blood parasites with a sensitivity comparable to real-time PCR. To date, the efficacy of this assay has only been assessed on human blood. This study assessed the utility of nUPDx for the detection of parasitic infections in animals using blood, tissues, and other biological sample types from mammals, birds, and reptiles, known to be infected with helminth, apicomplexan, or pentastomid parasites (confirmed by microscopy or PCR), as well as negative samples. nUPDx confirmed apicomplexan and/or nematode infections in 24 of 32 parasite-positive mammals, while also identifying several undetected coinfections. nUPDx detected infections in 6 of 13 positive bird and 1 of 2 positive reptile samples. When applied to 10 whole parasite specimens (worms and arthropods), nUPDx identified all to the genus or family level, and detected one incorrect identification made by morphology. Babesia sp. infections were detected in 5 of the 13 samples that were negative by other diagnostic approaches. While nUPDx did not detect PCR/microscopy-confirmed trichomonads or amoebae in cloacal swabs/tissue from 8 birds and 2 reptiles due to primer template mismatches, 4 previously undetected apicomplexans were detected in these samples. Future efforts to improve the utility of the assay should focus on validation against a larger panel of tissue types and animal species. Overall, nUPDx shows promise for use in both veterinary diagnostics and wildlife surveillance, especially because species-specific PCRs can miss unknown or unexpected pathogens.

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).

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.

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.

Assessing an Adaptation of the Universal Parasite Diagnostic Assay for Bloodborne Parasites in a US State Public Health Laboratory.

For complex clinical cases where a parasitic infection is suspected, it can be difficult for clinicians to recommend an appropriate laboratory test. These tests are usually pathogen-specific and require a certain degree of suspicion for the precise etiology. A recently described assay, the universal parasite diagnostic (UPDx) can potentially provide a diagnosis of any parasite present in a specimen. Using primers that amplify DNA from all eukaryotes, UPDx differentiates several parasitic infections in blood by amplicon-based next-generation sequencing (NGS) of the 18S rDNA locus. As the state's public health reference laboratory, the Parasitology Laboratory at the Wadsworth Center (Albany, NY) receives specimens from patients who have potentially encountered a wide variety of parasites. As such, the ability to differentiate several blood parasites using a single assay is of interest. We assessed UPDx for its ability to confirm parasitic infections for 20 specimens that were previously identified by real-time PCR (RT-PCR). This included specimens positive for Babesia microti, Trypanosoma cruzi, Leishmania tropica, various Plasmodium species, and specimens comprising mixed Plasmodium sp. infections. Results obtained using UPDx were largely concordant with the RT-PCR assays. A T. cruzi positive specimen was negative by UPDx and for two mixed Plasmodium sp. infections only one species was detected. The results obtained for other specimens were concordant. We conclude that UPDx shows promise for the detection of blood parasites in diagnostic laboratories. As NGS becomes cheaper, assays like UPDx will become increasingly amenable to use in clinical settings.

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.

Correction: A global genotyping survey of Strongyloides stercoralis and Strongyloides fuelleborni using deep amplicon sequencing.

[This corrects the article DOI: 10.1371/journal.pntd.0007609.].

A new subspecies of Trypanosoma cyclops found in the Australian terrestrial leech Chtonobdella bilineata.

Previously, it was suggested that haemadipsid leeches represent an important vector of trypanosomes amongst native animals in Australia. Consequently, Chtonobdella bilineata leeches were investigated for the presence of trypanosome species by polymerase chain reaction (PCR), DNA sequencing and in vitro isolation. Phylogenetic analysis ensued to further define the populations present. PCR targeting the 28S rDNA demonstrated that over 95% of C. bilineata contained trypanosomes; diversity profiling by deep amplicon sequencing of 18S rDNA indicated the presence of four different clusters related to the Trypanosoma (Megatrypanum) theileri. Novy­MacNeal­Nicolle slopes with liquid overlay were used to isolate trypanosomes into culture that proved similar in morphology to Trypanosoma cyclops in that they contained a large numbers of acidocalcisomes. Phylogeny of 18S rDNA/GAPDH/ND5 DNA sequences from primary cultures and subclones showed the trypanosomes were monophyletic, with T. cyclops as a sister group. Blood-meal analysis of leeches showed that leeches primarily contained blood from swamp wallaby (Wallabia bicolour), human (Homo sapiens) or horse (Equus sp.). The leech C. bilineata is a host for at least five lineages of Trypanosoma sp. and these are monophyletic with T. cyclops; we propose Trypanosoma cyclops australiensis as a subspecies of T. cyclops based on genetic similarity and biogeography considerations.

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.