ORCID
https://orcid.org/https://orcid.org/0000-0001-8882-8897
Date of Award
Summer 8-15-2018
Degree Name
Doctor of Philosophy (PhD)
Degree Type
Dissertation
Abstract
Undernutrition is the leading cause of child mortality worldwide. Moreover, children who survive periods of undernutrition suffer long-term consequences including stunted growth, greater susceptibility to infection, and cognitive deficiencies. Therefore, undernutrition is a substantial public health and economic burden that limits human potential in low-income countries. An increasing body of evidence posits that Ԯormalՠgut community (microbiota) development is linked to healthy growth; however, therapeutic foods currently used to treat undernutrition were not designed considering the impact on the developing gut microbiota. We hypothesized that by treating undernourished children with microbiota-directed therapeutic foods to repair their gut microbiota immaturity, we could improve outcomes such as gut barrier function, immune function, metabolism, and growth.
Here, I combined culture-independent V4-16S sequencing and machine learning to generate models of normal gut microbiota development for healthy birth cohorts from five low-income countries and reveal a shared program of microbiota assembly over the first two years of life that is independent of individualsՠculture or geography. Applying these models to bacterial V4-16S datasets from Bangladeshi children treated for severe acute malnutrition (SAM) confirms the finding that children with undernutrition harbor immature microbial gut communities that are not repaired by existing therapeutic foods. ԁge-discriminatoryՠbacterial taxa identified in these models and taxa enriched in individuals with SAM were subsequently cultured from fecal samples from Bangladeshi children. Gnotobiotic mice were colonized with these sequenced bacterial strains and fed different combinations and sequences of Bangladeshi complementary food (CF) ingredients; the results revealed ingredients that could specifically increase the relative abundance of targeted age-discriminatory bacterial taxa. Lead ingredients from this screen were combined in a microbiota-directed complementary food (MDCF) prototype which, compared to an existing therapeutic food, selectively increased the abundance of targeted taxa and increased biomarkers of growth in gnotobiotic mice.
To obtain a deeper understanding of the biological state of undernutrition, we performed proteomic and metabolomic analyses of plasma samples and characterized the gut microbial communities of Bangladeshi children treated for SAM and followed over the course of a 12- month study during which time many transitioned to a state of moderate acute malnutrition (MAM). There were significant correlations between plasma protein biomarkers of growth and immune function and age-discriminatory taxa in the gut microbiota of these children. MDCF prototypes were subsequently tested in gnotobiotic mice colonized with a representative post-SAM MAM microbiota and in gnotobiotic piglets colonized with a defined consortium of targeted age- and growth-discriminatory bacteria. The results revealed that these MDCF prototypes were able to increase the representation of targeted age- and growth-discriminatory taxa, alter their patterns of gene expression, improve gut barrier function in recipient mice, and increase growth in piglets. Finally, a randomized, double blind study was performed to test the effects of three MDCF formulations in Bangladeshi children with MAM. A lead MDCF changed the levels of biomarkers and mediators of growth, bone formation, neurodevelopment, and immune function toward a healthy state. These changes in the host proteome were accompanied by MDCF-induced changes in the configuration of the gut microbiota.
Language
English (en)
Chair and Committee
Jeffrey I. Gordon
Committee Members
Dan Goldberg, Scott Hultgren, Lora Iannotti, Rob Mitra,
Recommended Citation
Gehrig, Jeanette Lynn, "Microbiota-Directed Therapeutic Foods for the Treatment of Childhood Undernutrition" (2018). Arts & Sciences Electronic Theses and Dissertations. 1622.
https://openscholarship.wustl.edu/art_sci_etds/1622
Comments
Permanent URL: 2019-08-02