Blastocystis One Health Approach in a Rural Community of Northern Thailand: Prevalence, Subtypes and Novel Transmission Routes

Blastocystis is the most commonly found eukaryote in the gut of humans and other animals. This protist is extremely heterogeneous genetically and is classified into 28 subtypes (STs) based on the small subunit ribosomal RNA (SSU rRNA) gene. Numerous studies exist on prevalence of the organism, which usually focus on either humans or animals or the environment, while only a handful investigates all three sources simultaneously. Consequently, understanding of Blastocystis transmission dynamics remains inadequate. Our aim was to explore Blastocystis under the One Health perspective using a rural community in northern Thailand as our study area. We surveyed human, other animal and environmental samples using both morphological and molecular approaches. Prevalence rates of Blastocystis were 73% in human hosts (n = 45), 100% in non-human hosts (n = 44) and 91% in environmental samples (n = 35). Overall, ten subtypes were identified (ST1, ST2, ST3, ST4 ST5, ST6, ST7, ST10, ST23, and ST26), eight of which were detected in humans (ST1, ST2, ST3, ST4, ST5, ST7, ST10, and ST23), three in other animals (ST6, ST7, and ST23), while seven (ST1, ST3, ST6, ST7, ST10, ST23, and ST26) were found in the environment. In our investigation of transmission dynamics, we assessed various groupings both at the household and community level. Given the overall high prevalence rate, transmission amongst humans and between animals and humans are not as frequent as expected with only two subtypes being shared. This raises questions on the role of the environment on transmission of Blastocystis. Water and soil comprise the main reservoirs of the various subtypes in this community. Five subtypes are shared between humans and the environment, while three overlap between the latter and animal hosts. We propose soil as a novel route of transmission, which should be considered in future investigations. This study provides a thorough One Health perspective on Blastocystis. Using this type of approach advances our understanding on occurrence, diversity, ecology and transmission dynamics of this poorly understood, yet frequent gut resident

Molecular Identification of Cryptosporidium spp., and Giardia duodenalis in Dromedary Camels (Camelus dromedarius) from the Algerian Sahara

(1) Intestinal microbial parasites are major contributors to the global burden of gastrointestinal disease. Such infections are mainly caused by Cryptosporidium, Giardia duodenalis, and Entamoeba histolytica. These parasites are transmitted either directly or indirectly through oral–fecal routes. Previous reports suggested that camels could play a role in the zoonotic transmission of various clinically and veterinary important intestinal parasites, however, limited data are available on intestinal infections of camels, particularly on a molecular level. We aimed to explore the occurrence of these three parasites in camels (Camelus dromedarius) in Algeria. (2) A total of 68 samples—63 stool samples from camels and five from the environment—were collected from two desert regions in Algeria and analyzed using PCR and qPCR methods. (3) Overall, 7% of the camels tested positive for zoonotic subtypes of Cryptosporidium spp., while 16% of the camels tested positive for G. duodenalis. Two environmental samples also tested positive for G. duodenalis. None of the samples were positive for Entamoeba histolytica. (4) Our results provide one of the first molecular-based identification of these gut parasites in dromedary camels in Algeria. The presence of G. duodenalis in the host and the environment unveils, in part, the circulation route of this parasite. Our results will spearhead further investigations into the prevalence and epidemiology of gut parasites in hoofed animals and raise questions concerning their role in health and disease in the area

BioGAN: An unpaired GAN-based image to image translation model for microbiological images

Background and objective: A diversified dataset is crucial for training a well-generalized supervised computer vision algorithm. However, in the field of microbiology, generation and annotation of a diverse dataset including field-taken images are time-consuming, costly, and in some cases impossible. Image to image translation frameworks allow us to diversify the dataset by transferring images from one domain to another. However, most existing image translation techniques require a paired dataset (original image and its corresponding image in the target domain), which poses a significant challenge in collecting such datasets. In addition, the application of these image translation frameworks in microbiology] is rarely discussed . In this study, we aim to develop an unpaired GAN-based (Generative Adversarial Network) image to image translation model for microbiological images, and study how it can improve generalization ability of object detection models. Methods: In this paper, we present an unpaired and unsupervised image translation model to translate laboratory-taken microbiological images to field images, building upon the recent advances in GAN networks and Perceptual loss function. We propose a novel design for a GAN model, BioGAN, by utilizing Adversarial and Perceptual loss in order to transform high level features of laboratory-taken images of Prototheca bovis into field images, while keeping their spatial features. Results: We studied the contribution of Adversarial and Perceptual loss in the generation of realistic field images. We used the synthetic field images, generated by BioGAN, to train an object-detection framework, and compared the results with those of an object-detection framework trained with laboratory images; this resulted in up to 68.1% and 75.3% improvement on F1score and mAP, respectively. We also present the results of a qualitative evaluation test, performed by experts, of the similarity of BioGAN synthetic images with field images

Presence of Cryptosporidium parvum in pre-washed vegetables from different supermarkets in South East England: A pilot study

Cryptosporidium is an important water-borne and food-borne parasite with a high burden of disease. This organism has been shown to contaminate various leafy vegetables; however, studies assessing the presence of Cryptosporidium spp in pre-washed and ready-to-eat vegetables are limited. Routine surveillance in the UK revealed a nationwide exceedance of human cases of Cryptosporidium. Therefore, this study aims to assess the presence of this parasite in pre-washed vegetables from supermarkets in the UK. A total of 36 samples were purchased from four different supermarkets. A nested PCR targeting the SSU rRNA was carried out on 24 samples, 58% were PCR-positive for Cryptosporidium. Sanger sequencing confirmed that, of these sequences, 4/24 (17%) produced significant similarities to Cryptosporidium parvum. This study provides evidence for the presence of C. parvum in pre-washed and ready-to-eat vegetables. Future work to identify the point of contamination is required

First Epidemiological Report on the Prevalence and Associated Risk Factors of Cryptosporidium spp. in Farmed Marine and Wild Freshwater Fish in Central and Eastern of Algeria

Purpose The present study aimed to estimate the prevalence and molecular characterization of Cryptosporidium spp. in six different fish species both from marine and freshwater environments. Methods During a period of 2 years (2018–2020), a total of 415 fecal samples and 565 intestinal scrapings were collected in seven provinces from the central and eastern Algeria. From those, 860 fish belonged to six different species, two of which are cultured marine and four are wild freshwater fish. All samples were screened for Cryptosporidium spp. presence using molecular techniques. Nested PCR approach was performed to amplify partial sequences of the small subunit ribosomal RNA (SSU rRNA) and 60-kDa glycoprotein (GP60) genes for Cryptosporidium genotyping and subtyping. Detailed statistical analysis was performed to assess the prevalence variation of Cryptosporidium infection according to different risk factors. Results Nested PCR analysis of SSU gene revealed 173 Cryptosporidium positive fish, giving an overall prevalence of 20.11% (17.5–23.0). Cryptosporidium spp. was detected in 8.93% (42/470) of cultured marine fish and 33.58% (131/390) of wild freshwater fish. Overall, the prevalence was affected by all studied risk factors, except the gender. Molecular characterization and subtyping of Cryptosporidium isolates showed occurrence of IIaA16G2R1 and IIaA17G2R1 subtypes of C. parvum in the fish species Sparus aurata. Conclusion The present study provides the first epidemiological data on the prevalence and associated risk factors of Cryptosporidium spp. in farmed marine and wild freshwater fish and the first molecular data on the occurrence of zoonotic C. parvum in fish from North Africa (Algeria)