Dataset Information

Presence of Cryptosporidium parvum and Giardia lamblia in water samples from Southeast Asia: towards an integrated water detection system.

ABSTRACT: Access to clean and safe drinking water that is free from pathogenic protozoan parasites, especially Cryptosporidium parvum and Giardia lamblia that cause gastrointestinal illness in humans, is still an issue in Southeast Asia (SEA). This study is the first attempt to detect the aforementioned protozoan parasites in water samples from countries in SEA, using real-time polymerase chain reaction (qPCR) assays.A total of 221 water samples of 10 l each were collected between April and October 2013 from Malaysia (53), Thailand (120), the Philippines (33), and Vietnam (15). A physicochemical analysis was conducted. The water samples were processed in accordance with the US Environmental Protection Agency's methods 1622/1623.1, microscopically observed and subsequently screened using qPCR assays.Cryptosporidium oocysts were detected in treated water samples from the Philippines (1/10), with a concentration of 0.06?±?0.19 oocyst/L, and untreated water samples from Thailand (25/93), Malaysia (17/44), and the Philippines (11/23), with concentrations ranging from 0.13?±?0.18 to 0.57?±?1.41 oocyst/L. Giardia cysts were found in treated water samples from the Philippines (1/10), with a concentration of 0.02?±?0.06 cyst/L, and in untreated water samples from Thailand (20/93), Vietnam (5/10), Malaysia (22/44), and the Philippines (16/23), with concentrations ranging from 0.12?±?0.3 to 8.90?±?19.65 cyst/L. The pathogens C. parvum and G. lamblia were detected using using qPCR assays by targeting the 138-bp fragment and the small subunit gene, respectively. C. parvum was detected in untreated water samples from the Philippines (1/23) and Malaysia (2/44), whilst, G. lamblia detected was detected in treated water samples from the Philippines (1/10) and in untreated water samples from Thailand (21/93), Malaysia (12/44), and the Philippines (17/23). Nitrate concentration was found to have a high positive correlation with (oo)cyst (0.993).The presence of (oo)cysts in the water samples means that there is potential risk for zoonotic disease transmission in the studied countries. Detection using qPCR is feasible for quantifying both pathogenic C. parvum and G. lamblia in large water samples.

SUBMITTER: Kumar T

PROVIDER: S-EPMC4712598 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Presence of Cryptosporidium parvum and Giardia lamblia in water samples from Southeast Asia: towards an integrated water detection system.

Kumar Thulasi T Abd Majid Mohamad Azlan MA Onichandran Subashini S Jaturas Narong N Andiappan Hemah H Salibay Cristina C CC Tabo Hazel A L HA Tabo Norbel N Dungca Julieta Z JZ Tangpong Jitbanjong J Phiriyasamith Sucheep S Yuttayong Boonyaorn B Polseela Raxsina R Do Binh Nhu BN Sawangjaroen Nongyao N Tan Tian-Chye TC Lim Yvonne A L YA Nissapatorn Veeranoot V

Infectious diseases of poverty 20160113

<h4>Background</h4>Access to clean and safe drinking water that is free from pathogenic protozoan parasites, especially Cryptosporidium parvum and Giardia lamblia that cause gastrointestinal illness in humans, is still an issue in Southeast Asia (SEA). This study is the first attempt to detect the aforementioned protozoan parasites in water samples from countries in SEA, using real-time polymerase chain reaction (qPCR) assays.<h4>Methods</h4>A total of 221 water samples of 10 l each were collect ...[more]

PMID: 26763230

Similar Datasets

Project description:BackgroundAlthough enteroparasites are common causes of diarrheal illness, few studies have been performed among children in Tanzania. This study aimed to investigate the prevalence of Cryptosporidium parvum/hominis, Entamoeba histolytica and Giardia lamblia among young children in Dar es Salaam, Tanzania, and identify risk factors for infection.Methodology/principal findingsWe performed an unmatched case-control study among children < 2 years of age in Dar es Salaam, recruited from August 2010 to July 2011. Detection and identification of protozoans were done by PCR techniques on DNA from stool specimens from 701 cases of children admitted due to diarrhea at the three study hospitals, and 558 controls of children with no history of diarrhea during the last month prior to enrollment. The prevalence of C. parvum/hominis was 10.4% (84.7% C. hominis), and that of G. lamblia 4.6%. E. histolytica was not detected. The prevalence of Cryptosporidium was significantly higher in cases (16.3%) than in controls (3.1%; P < 0.001; OR = 6.2; 95% CI: 3.7-10.4). G. lamblia was significantly more prevalent in controls (6.1%) than in cases (3.4%; P = 0.027; OR = 1.8; 95% CI: 1.1-3.1). Cryptosporidium infection was found more often in HIV-positive (24.2%) than in HIV-negative children (3.9%; P < 0.001; OR = 7.9; 95% CI: 3.1-20.5), and was also associated with rainfall (P < 0.001; OR = 2.41; 95% CI: 1.5-3.8). Among cases, stunted children had significantly higher risk of being infected with Cryptosporidium (P = 0.011; OR = 2.12; 95% CI: 1.2-3.8). G. lamblia infection was more prevalent in the cool season (P = 0.004; OR = 2.2; 95% CI: 1.3-3.8), and more frequent among cases aged > 12 months (P = 0.003; OR = 3.5; 95% CI: 1.5-7.8). Among children aged 7-12 months, those who were breastfed had lower prevalence of G. lamblia infection than those who had been weaned (P = 0.012).ConclusionsCryptosporidium infection is common among young Tanzanian children with diarrhea, particularly those living with HIV, and infection is more frequent during the rainy season. G. lamblia is frequently implicated in asymptomatic infections, but rarely causes overt diarrheal illness, and its prevalence increases with age.

Dataset Information

Presence of Cryptosporidium parvum and Giardia lamblia in water samples from Southeast Asia: towards an integrated water detection system.

Publications

Presence of Cryptosporidium parvum and Giardia lamblia in water samples from Southeast Asia: towards an integrated water detection system.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets