Logo Logo
  • Home
  • Publications
  • Meet Our Team
  • Contact

More Info

  • Email papinlab@virgina.edu
  • Phone Office: (434) 924-8195 Computational lab: (434) 982-6267 Wet lab: (434) 924-8640
  • Location 415 Lane Road, Room 2041 Charlottesville, VA 22903

Related Links

  • PubMed
  • UVA Engineering

Connect With Us

Increased Urinary Trimethylamine N-Oxide Following Cryptosporidium Infection and Protein Malnutrition Independent of Microbiome Effects

  • Home
  • Blog Details
May 19 2017
  • Published Works

J Infect Dis. 2017 Jul 1;216(1):64-71. doi: 10.1093/infdis/jix234.

ABSTRACT

Cryptosporidium infections have been associated with growth stunting, even in the absence of diarrhea. Having previously detailed the effects of protein deficiency on both microbiome and metabolome in this model, we now describe the specific gut microbial and biochemical effects of Cryptosporidium infection. Protein-deficient mice were infected with Cryptosporidium parvum oocysts for 6-13 days and compared with uninfected controls. Following infection, there was an increase in the urinary excretion of choline- and amino-acid-derived metabolites. Conversely, infection reduced the excretion of the microbial-host cometabolite (3-hydroxyphenyl)propionate-sulfate and disrupted metabolites involved in the tricarboxylic acid (TCA) cycle. Correlation analysis of microbial and biochemical profiles resulted in associations between various microbiota members and TCA cycle metabolites, as well as some microbial-specific degradation products. However, no correlation was observed between the majority of the infection-associated metabolites and the fecal bacteria, suggesting that these biochemical perturbations are independent of concurrent changes in the relative abundance of members of the microbiota. We conclude that cryptosporidial infection in protein-deficient mice can mimic some metabolic changes seen in malnourished children and may help elucidate our understanding of long-term metabolic consequences of early childhood enteric infections.

PMID:28520899 | PMC:PMC5905612 | DOI:10.1093/infdis/jix234

Previous Post Next Post

Recent Posts

  • Metabolic modeling of sex-specific tissue predicts mechanisms of differences in toxicological responses
  • Identifying metabolic shifts in Crohn’s disease using’ omics-driven contextualized computational metabolic network models
  • Ten simple rules for launching an academic research career
  • Metabolic Network Models of the Gardnerella Pangenome Identify Key Interactions with the Vaginal Environment
  • Enterococci enhance Clostridioides difficile pathogenesis
Logo

Computational Systems Biology Laboratory; The research group of Dr. Jason Papin in the Department of Biomedical Engineering at the University of Virginia.

Related Links

  • PubMed
  • UVA Engineering

Contact Info

The research group of Dr. Jason Papin in the Department of Biomedical Engineering at the University of Virginia

  • Email: papinlab@virginia.edu
  • Phone (434) 924-8195

  • Home
  • Publications
  • Meet Our Team
  • Contact