Read Cloud Sequencing Elucidates Microbiome Dynamics in a Stem Cell Transplant Patient

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Low intestinal microbial diversity, often leading to domination of the intestine by a single organism, is associated with poor outcomes following stem cell transplantation. However, the process by which certain organisms achieve domination over others is not well-understood. Previously, it has been difficult to obtain genetic clues as to why the dominating organism has such high fitness in a given circumstance. This is because it has been nearly impossible to obtain near complete genome drafts of the dominating organism without isolation and culturing. Recently, we developed a metagenomic read cloud sequencing approach, which provides significantly improved genome drafts for individual organisms compared to commonly used alternative sequencing methods. Here, we apply read cloud sequencing to stool samples collected longitudinally from a stem cell transplant patient before and after heavy antibiotic exposure across four time points, during which the patient experienced a period of gut domination by E. coli as well as an E. coli bloodstream infection. Comparative genomic analysis reveals that the E. coli strain present in the gut and the E. coli strain isolated from the bloodstream infection are nearly identical (~99.97 nucleotide identity with a difference of 169 SNPs), indicating that the infection likely originated from the gut. Alignment of the pre-transplant E. coli draft genome to the Comprehensive Antibiotic Resistance Database reveals that the pre-transplant E. coli strain (prior to any antibiotic exposure) harbored 55 known resistance genes, including fluoroquinolone resistance and a multitude of multidrug efflux pumps. All other draft genomes from the pre-transplant time point contained <5 resistance genes, suggesting that the E. coli outgrowth was a result of selection after heavy antibiotic exposure. This case study highlights the application of metagenomic read cloud sequencing in a clinical context to investigate microbiome dynamics under extreme selective pressures.


Type of resource text
Date created [ca. May 8, 2018]


Author Kang, Joyce Blossom
Primary advisor Bhatt, Ami S.
Advisor Kundaje, Anshul B.
Degree granting institution Stanford University, Department of Computer Science


Subject Metagenomics
Subject read cloud sequencing
Subject genome assembly
Subject microbiome
Subject antibiotic resistance
Subject stem cell transplantation
Subject Computer Science
Genre Thesis

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This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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Kang, Joyce. (2018). Read Cloud Sequencing Elucidates Microbiome Dynamics in a Stem Cell Transplant Patient. Stanford Digital Repository. Available at:


Undergraduate Theses, School of Engineering

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