A novel, stain-free, natural auto-fluorescent signal, Sig M, identified from cytometric and transcriptomic analysis of infectivity of Cryptosporidium hominis and Cryptosporidium parvum.

Cryptosporidiosis is a worldwide diarrheal disease caused by the protozoan Cryptosporidium. The primary symptom is diarrhea, but patients may exhibit different symptoms based on the species of the Cryptosporidium parasite they are infected with. Furthermore, some genotypes within species are more transmissible and apparently virulent than others. The mechanisms underpinning these differences are not understood, and an effective in vitro system for Cryptosporidium culture would help advance our understanding of these differences. Using COLO-680N cells, we employed flow cytometry and microscopy along with the C. parvum-specific antibody Sporo-Glo™ to characterize infected cells 48 h following an infection with C. parvum or C. hominis. The Cryptosporidium parvum-infected cells showed higher levels of signal using Sporo-Glo™ than C. hominis-infected cells, which was likely because Sporo-Glo™ was generated against C. parvum. We found a subset of cells from infected cultures that expressed a novel, dose-dependent auto-fluorescent signal that was detectable across a range of wavelengths. The population of cells that expressed this signal increased proportionately to the multiplicity of infection. The spectral cytometry results confirmed that the signature of this subset of host cells closely matched that of oocysts present in the infectious ecosystem, pointing to a parasitic origin. Present in both C. parvum and C. hominis cultures, we named this Sig M, and due to its distinct profile in cells from both infections, it could be a better marker for assessing Cryptosporidium infection in COLO-680N cells than Sporo-Glo™. We also noted Sig M's impact on Sporo-Glo™ detection as Sporo-Glo™ uses fluoroscein-isothiocynate, which is detected where Sig M also fluoresces. Lastly, we used NanoString nCounter® analysis to investigate the transcriptomic landscape for the two Cryptosporidium species, assessing the gene expression of 144 host and parasite genes. Despite the host gene expression being at high levels, the levels of putative intracellular Cryptosporidium gene expression were low, with no significant difference from controls, which could be, in part, explained by the abundance of uninfected cells present as determined by both Sporo-Glo™ and Sig M analyses. This study shows for the first time that a natural auto-fluorescent signal, Sig M, linked to Cryptosporidium infection can be detected in infected host cells without any fluorescent labeling strategies and that the COLO-680N cell line and spectral cytometry could be useful tools to advance the understanding of Cryptosporidium infectivity.

Diagnosis of protozoa diarrhoea in Campylobacter patients increases markedly with molecular techniques.

Cryptosporidium and Giardia are major causes of diarrhoea globally, and two of the most notified infectious diseases in New Zealand. Diagnosis requires laboratory confirmation carried out mostly via antigen or microscopy-based techniques. However, these methods are increasingly being superseded by molecular techniques. Here we investigate the level of protozoa detection by molecular methods in campylobacteriosis cases missed through antigen-based assays and investigate different molecular testing protocols. We report findings from two observational studies; the first among 111 people during a Campylobacter outbreak and the second during normal surveillance activities among 158 people presenting with diarrhoea and a positive Campylobacter test, but negative Cryptosporidium and Giardia antigen-based test results. The molecular methods used for comparison were in-house end-point PCR tests targeting the gp60 gene for Cryptosporidium and gdh gene for Giardia. DNA extraction was performed with and without bead-beating and comparisons with commercial real-time quantitative (qPCR) were made using clinical Cryptosporidium positive sample dilutions down to 10-5. The Cryptosporidium prevalence was 9% (95% CI: 3-15; 10/111) and Giardia prevalence 21% (95% CI: 12-29; 23/111) in the 111 Campylobacter outbreak patients. The Cryptosporidium prevalence was 40% (95% CI: 32-48; 62/158) and Giardia prevalence 1.3% (95% CI: 0.2-4.5; 2/158) in the 158 routine surveillance samples. Sequencing identified Cryptosporidium hominis, C. parvum, and Giardia intestinalis assemblages A and B. We found no statistical difference in positive test results between samples using end-point PCR with or without bead-beating prior to DNA extraction, or between the in-house end-point PCR and qPCR. The qPCR Ct value was 36 (95% CI: 35-37) for 1 oocyst, suggesting a high limit of detection. In conclusion in surveillance and outbreak situations we found diagnostic serology testing underdiagnoses Cryptosporidium and Giardia coinfections in Campylobacter patients, suggesting the impact of protozoa infections may be underestimated through underdiagnosis using antigen-based assays.

Uncovering the genetic diversity of Giardia intestinalis in isolates from outbreaks in New Zealand.

BACKGROUND: Giardia intestinalis is one of the most common causes of diarrhoea worldwide. Molecular techniques have greatly improved our understanding of the taxonomy and epidemiology of this parasite. Co-infection with mixed (sub-) assemblages has been reported, however, Sanger sequencing is sometimes unable to identify shared subtypes between samples involved in the same epidemiologically linked event, due to samples showing multiple dominant subtypes within the same outbreak. Here, we aimed to use a metabarcoding approach to uncover the genetic diversity within samples from sporadic and outbreak cases of giardiasis to characterise the subtype diversity, and determine if there are common sequences shared by epidemiologically linked cases that are missed by Sanger sequencing. METHODS: We built a database with 1109 unique glutamate dehydrogenase (gdh) locus sequences covering most of the assemblages of G. intestinalis and used gdh metabarcoding to analyse 16 samples from sporadic and outbreak cases of giardiasis that occurred in New Zealand between 2010 and 2018. RESULTS: There is considerable diversity of subtypes of G. intestinalis present in each sample. The utilisation of metabarcoding enabled the identification of shared subtypes between samples from the same outbreak. Multiple variants were identified in 13 of 16 samples, with Assemblage B variants most common, and Assemblages E and A present in mixed infections. CONCLUSIONS: This study showed that G. intestinalis infections in humans are frequently mixed, with multiple subtypes present in each host. Shared sequences among epidemiologically linked cases not identified through Sanger sequencing were detected. Considering the variation in symptoms observed in cases of giardiasis, and the potential link between symptoms and (sub-) assemblages, the frequency of mixed infections could have implications for our understanding of host-pathogen interactions.