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Influence of Feeding Type on Gut Microbiome Development in Hospitalized Preterm Infants

Cong, Xiaomei; Judge, Michelle; Xu, Wanli; Diallo, Ana; Janton, Susan; Brownell, Elizabeth A.; Maas, Kendra; Graf, Joerg

doi: 10.1097/NNR.0000000000000208
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Background Premature infants have a high risk for dysbiosis of the gut microbiome. Mother’s own milk (MOM) has been found to favorably alter gut microbiome composition in infants born at term. Evidence about the influence of feeding type on gut microbial colonization of preterm infants is limited.

Objective The purpose of this study was to explore the effect of feeding types on gut microbial colonization of preterm infants in the neonatal intensive care unit.

Methods Thirty-three stable preterm infants were recruited at birth and followed up for the first 30 days of life. Daily feeding information was used to classify infants into six groups (MOM, human donor milk [HDM], Formula, MOM + HDM, MOM + Formula, and HDM + Formula) during postnatal days 0–10, 11–20, and 21–30. Stool samples were collected daily. DNA extracted from stool was used to sequence the 16S rRNA gene. Exploratory data analysis was conducted with a focus on temporal changes of microbial patterns and diversities among infants from different feeding cohorts. Prediction of gut microbial diversity from feeding type was estimated using linear mixed models.

Results Preterm infants fed MOM (at least 70% of the total diet) had highest abundance of Clostridiales, Lactobacillales, and Bacillales compared to infants in other feeding groups, whereas infants fed primarily HDM or formula had a high abundance of Enterobacteriales compared to infants fed MOM. After controlling for gender, postnatal age, weight, and birth gestational age, the diversity of gut microbiome increased over time and was constantly higher in infants fed MOM relative to infants with other feeding types (p < .01).

Discussion MOM benefits gut microbiome development of preterm infants, including balanced microbial community pattern and increased microbial diversity in early life.

Xiaomei Cong, PhD, RN, is Associate Professor, School of Nursing, University of Connecticut, Storrs; Affiliated Faculty, Institute for Systems Genomics, University of Connecticut, Farmington; and Faculty, Department of Pediatrics, School of Medicine, University of Connecticut, Farmington.

Michelle Judge, PhD, RD, CD-N, is Assistant Professor; Wanli Xu, BSN, MS, RN, is PhD student; and Ana Diallo, MSN, RN, is PhD student, School of Nursing, University of Connecticut, Storrs.

Susan Janton, MS, is Technician, Department of Molecular and Cell Biology, University of Connecticut, Storrs.

Elizabeth A. Brownell, PhD, is Assistant Professor, Department of Pediatrics, School of Medicine, University of Connecticut, Farmington, and Perinatal Epidemiologist, Division of Neonatology, Connecticut Children’s Medical Center, Hartford.

Kendra Maas, PhD, is Facility Scientist, Microbial Analysis, Resources, and Services, University of Connecticut, Storrs.

Joerg Graf, PhD, is Professor, Department of Molecular and Cell Biology, University of Connecticut, Storrs and Institute for Systems Genomics, University of Connecticut, Farmington.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www.nursingresearchonline.com).

Accepted for publication November 3, 2016.

The authors thank the medical and nursing staff in the NICUs of Connecticut Children’s Medical Center at Hartford and Farmington, CT, for their support and assistance. We thank Victoria Vazquez, Shari Galvin, Megan Fitzsimons, Carrie-Ellen Briere, Dorothy Vittner, Stephanie Demaio, and Jessica Demaio for their assistance in recruiting subjects, collecting clinical data, managing stool sample collection and storage, and data management. We acknowledge the Microbial Analysis, Resources, and Services (MARS) facility at University of Connecticut for their ongoing support of this project.

This publication was supported by the National Institute of Nursing Research of the National Institutes of Health (NIH-NINR) under Award K23NR014674 and Affinity Research Collaboratives Award through University of Connecticut Institute for Systems Genomics.

X. Cong and J. Graf contributed to conception or design of the research; X. Cong, M. Judge, W. Xu, A. Diallo, K. Maas, S. Janton, and J. Graf contributed to acquisition, analysis, or interpretation of the data; and X. Cong, M. Judge, W. Xu, A. Diallo, E. Brownell, and J. Graf drafted the manuscript. All authors critically revised the manuscript, gave final approval, and agree to be accountable for all aspects of work ensuring integrity and accuracy.

Editorial Note. Dr. Jacquelyn Taylor was Action Editor for this paper.

The authors have no conflicts of interest to declare.

Corresponding author: Xiaomei Cong, PhD, RN, School of Nursing, University of Connecticut, 231 Glenbrook Road, Storrs, CT 06269-4026 (e-mail: xiaomei.cong@uconn.edu).

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