Superior Auto-Identification of Trypanosome Parasites by Using a Hybrid Deep-Learning Model

Trypanosomiasis is a significant public health problem in several regions across the world, including South Asia and Southeast Asia. The identification of ...

Chulalongkorn University

Malaria parasites in the phylum Apicomplexa (Order: Haemosporida) infect diverse vertebrates and invertebrate hosts. At least seven genera of haemosporidian parasites have been described to exclusively infect bats. Most of these parasites remain enigmatic with a poorly known host range. Here, we investigated 271 bats belonging to 21 species and seven families from six provinces of Thailand. Overall, 124 out of 271 bats (45.8%) were positive for haemosporidian parasites, while none had  based on microscopic examination of blood smears and PCR amplification. We obtained 19 distinct cytochrome b () nucleotide haplotypes of  from seven bat species (families: Craseonycteridae, Hipposideridae, Pteropodidae, and Rhinolophidae).  was found in four bat species (Craseonycteridae, Emballonuridae, Megadermatidae, and Pteropodidae) and  in two species (Emballonuridae, Vespertilionidae). Phylogenetic analysis inferred from  sequences placed  into 2 different clades. Most  infections were found in insectivorous bats and clustered together with a sequence from  in Cambodia (in subclade 1a). A single sequence of  obtained from a frugivorous bat, , was placed in the same clade with  from the same bat species previously reported in Malaysia (clade 2).  in these Thai bats were clearly separated from the African isolates previously reported in bats in the family Rhinolophidae.  from  was placed in a distinct clade (clade 2) from  isolated from  (clade 1) These results confirmed that at least two distinct species of  are found in Thailand Collectively,  presented no host specificity. Although  seemed to be infected by only  its respective parasite does not show specificity to only a single bat host.  and  seem to infect a narrower host range or are somehow restricted to bats in the families Vespertilionidae and Emballonuridae, respectively.

First molecular investigation of haemosporidian parasites in Thai bat species.

Haemosporidian infections in domestic chickens (Gallus gallus domesticus) are not only widely prevalent but also cause economic loss. Diagnosis is usually made by microscopic examination; however, the method has several drawbacks such as requiring an experienced microscopist, being unreliable when parasitemia is low and being unable to accurately differentiate between co-infections from multiple parasite species. Therefore, the current extent of haemosporidian infections might be underestimated and neglected. We have developed a novel multiplex PCR assay to simultaneously detect and differentiate between four haemosporidian parasites: Leucocytozoon caulleryi, Leucocytozoon sabrazesi, Plasmodium juxtanucleare and Plasmodium gallinaceum. Primers in the present study specifically amplified the corresponding targets with no cross-species amplification detected. The multiplex PCR exhibited a significantly greater detection rate when compared with microscopic examination (p =  0.0001). The results demonstrate that the detection rate of multiplex PCR for L. sabrazesi, P. juxtanucleare, and P. gallinaceum are all greater than that of microscopic examination with p =  0.002, 0.0001 and 0.004, respectively. Co-infections were also detected more effectively by multiplex PCR. We applied the current method to field samples originating from Nan, Prachinburi, and Chachoengsao Provinces. The current study revealed that positive rates of haemosporidian parasites in chickens in the three study sites ranging from 39.5%-93.8%. The present assay offers a timesaving option for molecular diagnosis instead of using singleplex PCRs for detecting the parasites individually. Within a single reaction, this assay would be a useful tool for the detection of avian haemosporidian parasites either single or under co-infection conditions and for large-scale epidemiology studies.

Development and application of a novel multiplex PCR assay for the differentiation of four haemosporidian parasites in the chicken Gallus gallus domesticus.

The infection of an avian malaria parasite (Plasmodium gallinaceum) in domestic chickens presents a major threat to the poultry industry because it causes economic loss in both the quality and quantity of meat and egg production. Computer-aided diagnosis has been developed to automatically identify avian malaria infections and classify the blood infection stage development. In this study, four types of deep convolutional neural networks, namely Darknet, Darknet19, Darknet19-448 and Densenet201 are used to classify P. gallinaceum blood stages. We randomly collected a dataset of 12,761 single-cell images consisting of three parasite stages from ten-infected blood films stained by Giemsa. All images were confirmed by three well-trained examiners. The study mainly compared several image classification models and used both qualitative and quantitative data for the evaluation of the proposed models. In the model-wise comparison, the four neural network models gave us high values with a mean average accuracy of at least 97%. The Darknet can reproduce a superior performance in the classification of the P. gallinaceum development stages across any other model architectures. Furthermore, the Darknet has the best performance in multiple class-wise classification, with average values of greater than 99% in accuracy, specificity, and sensitivity. It also has a low misclassification rate (< 1%) than the other three models. Therefore, the model is more suitable in the classification of P. gallinaceum blood stages. The findings could help us create a fast-screening method to help non-experts in field studies where there is a lack of specialized instruments for avian malaria diagnostics.

Classification for avian malaria parasite Plasmodium gallinaceum blood stages by using deep convolutional neural networks.

Haemoplasma is a trivial name for haemotropic Mycoplasma spp., which can attach to the surface of red blood cells leading to deformity and anaemia in a wide range of mammalian animals, including pigs. In Thailand, there is only one study that reported the occurrence of Mycoplasma suis without other haemoplasma species. In this study, we examined the molecular occurrence and genetic diversity of porcine haemoplasmas in Thai domestic pigs (Sus scrofa domesticus) from commercial farms using a PCR assay targeting the 16S rRNA gene, DNA sequencing, nucleotide sequence type (ntST) analysis and phylogenetic analysis. A total of 665 blood samples were collected from pigs at thirteen farms located in eight provinces of Thailand during 2019-2020. Genomic DNA was extracted from blood samples and tested by PCR. The frequency of haemoplasma infection was 37.1% (247/665, 95% CI: 33.5%-40.9%) in all pigs. Among 247 PCR positive samples, 194 were sequenced and analysed by nucleotide BLAST, ntST diversity, phylogenetic trees and ntST networks. The results of this genetic analysis indicated that at least four species with 27 nucleotide sequence types (Mycoplasma suis, Mycoplasma parvum, Candidatus Mycoplasma haemosuis and a putative novel species) of porcine haemoplasmas were identified. Thus, it appears that haemoplasmas show a high genetic diversity in the Thai pig population. In addition, a putative novel species was genetically characterized by other markers, namely, the 23S rRNA and RNase P RNA (rnpB) genes. For phylogenetic analysis, Candidatus Mycoplasma haemosuis was placed into the Mycoplasma haemofelis group, and the three remaining species were placed into the Mycoplasma suis group in all trees containing the 16S rRNA, 23S rRNA and rnpB genes. Further studies, such as pathobiology and epidemiology, should be conducted to better characterize this putative novel species.

Molecular detection and genetic analysis of porcine haemoplasmas in commercial pig farms from Thailand reveal a putative novel species.

Mycoplasma (M.) suis is a pathogenic hemotropic Mycoplasma sp. that causes acute hemolytic anemia or chronic infection in pigs. M. suis infection can be diagnosed using several methods, including molecular diagnosis such as conventional PCR (cPCR) and quantitative PCR (qPCR). In these cases, the common target is the 16S rRNA gene; however, this genetic marker cannot distinguish hemoplasma at the species level owing to high sequence identity. Therefore, the 23S rRNA gene has emerged as another target gene. Other than PCR, the loop-mediated isothermal amplification (LAMP) method can be applied for M. suis. The objective of the present study was to establish cPCR, TaqMan qPCR, and LAMP assays in which the 23S rRNA gene is used to detect M. suis infection in Thai domestic pigs. The analytical sensitivity of cPCR was determined as 7.46 × 10 copies/μl of plasmid DNA, whereas those of qPCR and LAMP were 7.46 × 10 copies/μl. There was no cross reaction with other pathogens in any of the assays. To evaluate the diagnostic performance of the assays, they were tested using 173 samples of genomic DNA. The detection percentage of M. suis infection was 24.86% (43/173; 95% CI: 18.61%-31.89%), 28.32% (49/173; 95% CI: 21.75%-35.66%), and 29.48% (51/173; 95% CI: 22.80%-36.88%) using cPCR, qPCR, and LAMP, respectively. Using qPCR as a reference assay, cPCR showed 81.63% sensitivity, 97.58% specificity, and an almost perfect level of agreement (kappa = 0.823). In comparison, LAMP showed 77.55% sensitivity, 89.52% specificity, and a substantial level of agreement (kappa = 0.662). All assays tested here could be applied in veterinary diagnostic laboratories for monitoring porcine health in the herds. Furthermore, the LAMP assay could be used as a screening test in farm practice without the need for any special equipment.

Establishment of molecular diagnostics targeting the 23S ribosomal RNA gene for the detection of Mycoplasma suis infection in Thai domestic pigs.

Despite the natural occurrences of human infections by Plasmodium knowlesi, P. cynomolgi, P. inui, and P. fieldi in Thailand, investigating the prevalence and genetic diversity of the zoonotic simian malaria parasites in macaque populations has been limited to certain areas. To address this gap, a total of 560 long-tailed macaques (Macaca fascicularis) and 20 southern pig-tailed macaques (M. nemestrina) were captured from 15 locations across 10 provinces throughout Thailand between 2018 and 2021 for investigation of malaria, as were 15 human samples residing in two simian-malaria endemic provinces, namely Songkhla and Satun, who exhibited malaria-like symptoms. Using PCR techniques targeting the mitochondrial cytb and cox1 genes coupled with DNA sequencing, 40 long-tailed macaques inhabiting five locations had mono-infections with one of the three simian malaria species. Most of the positive cases of macaque were infected with P. inui (32/40), while infections with P. cynomolgi (6/40) and P. knowlesi (2/40) were less common and confined to specific macaque populations. Interestingly, all 15 human cases were mono-infected with P. knowlesi, with one of them residing in an area with two P. knowlesi-infected macaques. Nucleotide sequence analysis showed a high level of genetic diversity in P. inui, while P. cynomolgi and P. knowlesi displayed limited genetic diversity. Phylogenetic and haplotype network analyses revealed that P. inui in this study was closely related to simian and Anopheles isolates from Peninsular Malaysia, while P. cynomolgi clustered with simian and human isolates from Asian countries. P. knowlesi, which was found in both macaques and humans in this study, was closely related to isolates from macaques, humans, and An. hackeri in Peninsular Malaysia, suggesting a sylvatic transmission cycle extending across these endemic regions. This study highlights the current hotspots for zoonotic simian malaria and sheds light on the genetic characteristics of recent isolates in both macaques and human residents in Thailand.

Zoonotic simian malaria parasites in free-ranging Macaca fascicularis macaques and human malaria patients in Thailand, with a note on genetic characterization of recent isolates.

Suchansa Thanee

Veterinary Parasitology Research Unit,
Faculty of Veterinary Science,
Veterinary Parasitology Research Unit, Faculty of Veterinary Science

Chulalongkorn University

Superior Auto-Identification of Trypanosome Parasites by Using a Hybrid Deep-Learning Model

Suchansa Thanee

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Veterinary Parasitology Research Unit,Faculty of Veterinary Science,Veterinary Parasitology Research Unit, Faculty of Veterinary Science

Chulalongkorn University

Superior Auto-Identification of Trypanosome Parasites by Using a Hybrid Deep-Learning Model

Veterinary Parasitology Research Unit,
Faculty of Veterinary Science,
Veterinary Parasitology Research Unit, Faculty of Veterinary Science