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A protocol to count Cryptosporidium oocysts by flow cytometry without antibody staining.

ABSTRACT: Cryptosporidiosis caused by the protozoan parasites Cryptosporidium hominis and C. parvum, threatens the lives of young children in developing countries. In veterinary medicine, C. parvum causes life-threatening diarrhea and dehydration in newborn dairy calves. Protocols to detect Cryptosporidium spp. oocysts using flow cytometry have been reported; however, these protocols use antibodies against the parasite and typically focus on detection of oocysts, not quantification. These techniques are not well-suited for studies that generate large variations in oocyst burdens because the amount of antibody required is proportional to the number of oocysts expected in samples. Also, oocysts are lost in washes in the staining protocol, reducing accuracy of oocyst counts. Moreover, these protocols require costly fluorochrome-conjugated monoclonal antibodies and are not optimal for studies involving large numbers of samples. Here we present an optimized protocol for purifying oocysts from mouse stool and intestine samples combined with a reliable method to quantify oocysts in a relatively pure population without the need for antibody staining. We used morphology (SSC-A vs FSC-A) and the innate characteristics of C. parvum oocysts compared to fecal and intestinal contaminants to develop a two-step gating strategy that can differentiate oocysts from debris. This method is a fast, reliable, and high-throughput technique to promote research projects on C. parvum infections in mice and potentially other animal hosts.

SUBMITTER: Sonzogni-Desautels K

PROVIDER: S-EPMC6443187 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Project description:Over the past years, gut microbiota became a major field of interest with increasing reports suggesting its association with a large number of human diseases. In this context, there is a major interest to develop analysis tools allowing simple and cost-effective population pattern analysis of these complex ecosystems to follow changes over time. Whereas sequence-based metagenomics profiling is widely used for microbial ecosystems characterization, it still requires time and specific expertise for analysis. Flow cytometry overcomes these disadvantages, providing key information on communities within hours. In addition, it can potentially be used to select, isolate and cultivate specific bacteria of interest. In this study, we evaluated the culturability of strictly anaerobic bacteria that were stained with a classical Live/Dead staining, and then sorted using flow cytometry under anaerobic conditions. This sorting of "viable" fraction demonstrated that 10-80% of identified "viable" cells of pure cultures of strictly anaerobic bacteria were culturable. In addition, we tested the use of a combination of labeled vancomycin and Wheat Germ Agglutinin (WGA) lectin to discriminate Gram-positive from Gram-negative bacteria in complex ecosystems. After validation on both aerobic/anaerobic facultative and strictly anaerobic bacteria, the staining methods were applied on complex ecosystems, revealing differences between culture conditions and demonstrating that minor pH variations have strong impacts on microbial community structure, which was confirmed by 16S rRNA gene sequencing. This combination of staining methods makes it possible to follow-up evolutions of complex microbial communities, supporting its future use as a rapid analysis tool in various applications. The flow cytometry staining method that was developed has the potential to facilitate the analysis of complex ecosystems by highlighting changes in bacterial communities' dynamics. It is assumed to be applicable as an efficient and fast approach to improve the control of processes linked to a wide range of ecosystems or known communities of bacterial species in both research and industrial contexts.

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A protocol to count Cryptosporidium oocysts by flow cytometry without antibody staining.

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