Department of Earth and Planetary Science, University of California, Berkeley, Berkeley, United States
Cindy J Castelle
Department of Earth and Planetary Science, University of California, Berkeley, Berkeley, United States
Itai Sharon
Department of Earth and Planetary Science, University of California, Berkeley, Berkeley, United States
Robyn Baker
Division of Newborn Medicine, Children's Hospital of Pittsburgh and Magee-Womens Hospital of UPMC, Pittsburgh, United States
Misty Good
Division of Newborn Medicine, Children's Hospital of Pittsburgh and Magee-Womens Hospital of UPMC, Pittsburgh, United States; Department of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, United States
Michael J Morowitz
Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, United States
Jillian F Banfield
Department of Earth and Planetary Science, University of California, Berkeley, Berkeley, United States
Premature infants are highly vulnerable to aberrant gastrointestinal tract colonization, a process that may lead to diseases like necrotizing enterocolitis. Thus, spread of potential pathogens among hospitalized infants is of great concern. Here, we reconstructed hundreds of high-quality genomes of microorganisms that colonized co-hospitalized premature infants, assessed their metabolic potential, and tracked them over time to evaluate bacterial strain dispersal among infants. We compared microbial communities in infants who did and did not develop necrotizing enterocolitis. Surprisingly, while potentially pathogenic bacteria of the same species colonized many infants, our genome-resolved analysis revealed that strains colonizing each baby were typically distinct. In particular, no strain was common to all infants who developed necrotizing enterocolitis. The paucity of shared gut colonizers suggests the existence of significant barriers to the spread of bacteria among infants. Importantly, we demonstrate that strain-resolved comprehensive community analysis can be accomplished on potentially medically relevant time scales.