Automated enumeration of Eimeria oocysts in feces for rapid coccidiosis monitoring

Smith, Mary K; Buhr, Diane L.; Dhlakama, Thabani A.; Dupraw, Diana; Fitz-Coy, Steve; Francisco, Alexandra; Ganesan, Arjun; Hubbard, Sue Ann; Nederlof, A.; Newman, Linnea J; Stoner, Matthew R; Teichmann, June; Voyta, John C.; Wooster, Robert; Zeygerman, Alla; Zwilling, Matthew F.; Kiss, Margaret M.

doi:10.1016/j.psj.2022.102252

Cited by 2 publications

(2 citation statements)

References 48 publications

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“…However, we found that the protocols used for sample preparation for these applications are complex, and the oocyst counts may be overestimated. A recent publication describes a fast and automated method for the enumeration of Eimeria oocysts [8]. None of the available protocols differentiates sporulated and non-sporulated oocysts.…”

Section: Discussionmentioning

confidence: 99%

“…Automatic and semi-automatic protocols, including molecular tests, cytometry, and digital image analysis, for the enumeration and identification of coccidia are available [7][8][9][10]. Most PCR reactions target the intergenic transcribed spacer region 1 (ITS1) of the ribosomal RNA (rRNA) gene operon [7], a multi-copy gene, which makes these protocols unsuitable for estimation of the relative abundance of species in mixed infections of Eimeria sp.…”

Section: Introductionmentioning

confidence: 99%

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Automated Image Analysis for Detection of Coccidia in Poultry

Kellogg,

Roberts,

Crespo

2024

Animals

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Coccidiosis, caused by the protozoan Eimeria sp., is one of the most common and costly diseases impacting the poultry industry. To establish effective control measures, it is essential to identify these protozoa. Typical methods for identifying and determining the severity of the protozoal infection include intestinal lesion scoring or enumeration of the protozoal oocysts in fecal samples. Standard analysis methods require highly skilled technicians or veterinarians to manually identify and manually enumerate these protozoal parasites. This process is labor intensive, time-consuming, and susceptible to human error. None of the current methods available, including molecular flow cytometry or even digital image analysis, can determine if an oocyst is sporulated or not. Oocysts are not infectious until they sporulate. The goal of this study was to design an automated model using Artificial Intelligence (AI) to expedite the process of enumeration, improve the efficiency and accuracy of the species identification, and determine the ability of the oocysts to infect. To this end, we trained and evaluated computer vision models based on the Mask RCNN neural network architecture. A model was trained to detect and differentiate three species and to determine sporulation for each (totaling six detection groups). This model achieved a mean relative percentage difference (RPD) of 5.64%, representing a slight overcount compared to manual counts, averaging across all groups. The mean RPD for each group individually fell within a range from −33.37% to 52.72%. These results demonstrate that these models were speedy and had high agreement with manual counts, with minimal processing of field-quality samples. These models also could differentiate the sporulation status of the oocysts, providing critical diagnostic information for potential field applications.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Automated Image Analysis for Detection of Coccidia in Poultry

Kellogg,

Roberts,

Crespo

2024

Animals

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The microneme adhesive repeat domain of MIC3 protein determined the site specificity of Eimeria acervulina, Eimeria maxima, and Eimeria mitis

Zhang,

Lu,

Zhang

et al. 2023

Front. Immunol.

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Understanding the determinants of host and tissue tropisms among parasites of veterinary and medical importance has long posed a substantial challenge. Among the seven species of Eimeria known to parasitize the chicken intestine, a wide variation in tissue tropisms has been observed. Prior research suggested that microneme protein (MIC) composed of microneme adhesive repeat (MAR) domain responsible for initial host cell recognition and attachment likely dictated the tissue tropism of Eimeria parasites. This study aimed to explore the roles of MICs and their associated MARs in conferring site-specific development of E. acervuline, E. maxima, and E. mitis within the host. Immunofluorescence assays revealed that MIC3 of E. acervuline (EaMIC3), MIC3 of E. maxima (EmMIC3), MIC3 of E. mitis (EmiMIC3), MAR3 of EaMIC3 (EaMIC3-MAR3), MAR2 of EmMIC3 (EmMIC3-MAR2), and MAR4 of EmiMIC3 (EmiMIC3-MAR4), exhibited binding capabilities to the specific intestinal tract where these parasites infect. In contrast, the invasion of sporozoites into host intestinal cells could be significantly inhibited by antibodies targeting EaMIC3, EmMIC3, EmiMIC3, EaMIC3-MAR3, EmMIC3-MAR2, and EmiMIC3-MAR4. Substitution experiments involving MAR domains highlighted the crucial roles of EaMIC3-MAR3, EmMIC3-MAR2, and EmiMIC3-MAR4 in governing interactions with host ligands. Furthermore, animal experiments substantiated the significant contribution of EmiMIC3, EmiMIC3-MAR4, and their polyclonal antibodies in conferring protective immunity to Eimeria-affiliated birds. In summary, EaMIC3, EmMIC3, and EmiMIC3 are the underlying factors behind the diverse tissue tropisms exhibited by E. acervuline, E. maxima, and E. mitis, and EaMIC3-MAR3, EmMIC3-MAR2, and EmiMIC3-MAR4 are the major determinants of MIC-mediated tissue tropism of each parasite. The results illuminated the molecular basis of the modes of action of Eimeria MICs, thereby facilitating an understanding and rationalization of the marked differences in tissue tropisms among E. acervuline, E. maxima, and E. mitis.

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Automated enumeration of Eimeria oocysts in feces for rapid coccidiosis monitoring

Cited by 2 publications

References 48 publications

Automated Image Analysis for Detection of Coccidia in Poultry

Automated Image Analysis for Detection of Coccidia in Poultry

The microneme adhesive repeat domain of MIC3 protein determined the site specificity of Eimeria acervulina, Eimeria maxima, and Eimeria mitis

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