BackgroundThere are multiple etiologies responsible for infectious gastroenteritis causing acute diarrhea which are often under diagnosed. Also acute diarrhea is one of the major causes of morbidity and mortality among children less than 5 years of age.MethodsIn our study, fecal samples (n = 130) were collected from children (<5 years) presenting with symptoms of acute diarrhea. Samples were screened for viral, bacterial, and parasitic etiologies. Rotavirus and Adenovirus were screened by immunochromatographic tests. Diarrheagenic Escherichia coli (EPEC, EHEC, STEC, EAEC, O157, O111), Shigella spp., Salmonella spp., Vibrio cholera, Cryptosporidium spp., and Giardia spp. were detected by gene-specific polymerase chain reaction.Results Escherichia coli was detected to be the major etiological agent (30.07%) followed by Rotavirus (26.15%), Shigella (23.84%), Adenovirus (4.61%), Cryptosporidium (3.07%), and Giardia (0.77%). Concurrent infections with two or more pathogens were observed in 44 of 130 (33.84%) cases with a predominant incidence particularly in <2-year-old children (65.90%) compared to children of 2–5 years age group (34.09%). An overall result showed significantly higher detection rates among children with diarrhea in both combinations of two as well as three infections concurrently (p = 0.004915 and 0.03917, respectively).ConclusionSuspecting possible multiple infectious etiologies and diagnosis of the right causative agent(s) can aid in a better pharmacological management of acute childhood diarrhea. It is hypothesized that in cases with concurrent infections the etiological agents might be complementing each other’s strategies of pathogenesis resulting in severe diarrhea that could be studied better in experimental infections.Electronic supplementary materialThe online version of this article (doi:10.1186/s13099-017-0166-0) contains supplementary material, which is available to authorized users.

Cryptosporidium parvum and Giardia lamblia are zoonotic enteric protozoa of significant health concern where sanitation, hygiene, and water supplies are inadequate. We examined 85 stool samples from diarrhea patients, 111 pooled fecal samples by species across seven domestic animal types, and water from tube wells (N = 207) and ponds (N = 94) across 60 villages in coastal Odisha, India, for Cryptosporidium oocysts and Giardia cysts to measure occurrence, concentration/shedding, and environmental loading rates. Oocysts/cysts were detected in 12% of diarrhea patients. Detection ranged from 0% to 35% for Cryptosporidium and 0% to 67% for Giardia across animal hosts. Animal loading estimates indicate the greatest contributors of environmental oocysts/cysts in the study region are cattle. Ponds were contaminated with both protozoa (oocysts: 37%, cysts: 74%), as were tube wells (oocysts: 10%, cysts: 14%). Future research should address the public health concern highlighted from these findings and investigate the role of domestic animals in diarrheal disease transmission in this and similar settings.

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Computational approaches to predict structure/function and other biological characteristics of proteins are becoming more common in comparison to the traditional methods in drug discovery. Cryptosporidiosis is a major zoonotic diarrheal disease particularly in children, which is caused primarily by Cryptosporidium hominis and Cryptosporidium parvum. Currently, there are no vaccines for cryptosporidiosis and recommended drugs are ineffective. With the availability of complete genome sequence of C. hominis, new targets have been recognized for the development of effective and better drugs and/or vaccines. We identified a unique hypothetical protein (TU502HP) in the C. hominis genome from the CryptoDB database. A three-dimensional model of the protein was generated using the Iterative Threading ASSEmbly Refinement server through an iterative threading method. Functional annotation and phylogenetic study of TU502HP protein revealed similarity with human transportin 3. The model is further subjected to a virtual screening study form the ZINC database compound library using the Dock Blaster server. A docking study through AutoDock software reported N-(3-chlorobenzyl)ethane-1,2-diamine as the best inhibitor in terms of docking score and binding energy. The reliability of the binding mode of the inhibitor is confirmed by a complex molecular dynamics simulation study using GROMACS software for 10 ns in the water environment. Furthermore, antigenic determinants of the protein were determined with the help of DNASTAR software. Our findings report a great potential in order to provide insights in the development of new drug(s) or vaccine(s) for treatment and prophylaxis of cryptosporidiosis among humans and animals.