Antibiotic resistant bacterial infections are a significant, modern epidemic causing >23,000 deaths and two million illnesses in the US, annually. To treat and prevent antibiotic resistant infections, we must understand the complementary issues of (i) how new antibiotic resistance emerges and (ii) how these organisms are transmitted. Traditionally, bloodstream infection-causing antibiotic resistant pathogens are thought to be passed directly to the bloodstream from patient-to-patient. We propose instead that three of the most prevalent pathogens, Escherichia coli, Enterococcus faecium, and Enterococcus faecalis are transmitted to and from the gut microbiome of hospitalized patients, a transformative concept. Recently, we (Bhatt, Banaei) showed that pathogen reservoirs may ?lie in wait? in the gut microbiome of hematopoietic cell transplantation (HCT) patients, eventually translocating into the bloodstream to cause infections (Tamburini et al, Nature Medicine 2018). Leveraging a skilled and dedicated multidisciplinary team of experts in microbial genomics tool development (Bhatt), Clinical Microbiology (Banaei) and Statistics/Genetics (Tang), we will investigate both gut-to-gut (aim 1) and gut-to-blood transmission (aim 3), and will also test hypothesis that the gut microbiome is a niche where E. coli and Enterococci can evolve new antibiotic resistance (aim 2). Others have demonstrated that shotgun sequencing methods can enable exquisite strain tracking of isolated and cultured bacterial pathogens (e.g. carbapenemase-producing Klebsiella pneumonia and XDR TB). Unfortunately, technical challenges have prevented simultaneous and accurate complete assembly of microbial genomes, and thus tracking of multiple organisms? genomes within complex gut microbiomes. Recently, we overcame this challenge by developing an innovative ?read cloud? sequencing approach to stitch together the genomes of individual bacteria directly from sequencing of a microbiome sample (Bishara et al, Nature Biotech 2018). We will apply this approach as well as meta-HiC, which can ?link? plasmids to chromosomal DNA, to a longitudinal stool specimen collection from 666 HCT patients cared for on the same hospital ward over 3 years (1552 samples; median 2/patient; 215 patients with 3 samples). Leveraging temporal, geospatial and clinical information, we will use this stool bank resource to test the hypotheses that (i) E. coli and Enterococci are transmitted between gut reservoirs of HCT patients and (ii) new antibiotic resistance can evolve in these common gut-dwelling pathogens in HCT patients. Thus, we will identify risk factors for microbiome transmission, quantify emergence of new antibiotic resistance in HCT patients, and determine hospital-wide transmission networks for three important pathogens. Identifying these networks will inform methods that hospitals use (such as isolation rooms and use of contact precautions) to limit bacterial transmission, as well as how clinicians perceive the downsides of antibiotic use in hospitalized patients by demonstrating the impact of antibiotics on the emergence of new antibiotic resistance.

Public Health Relevance

Antibiotic resistant infections are a modern epidemic and transmission of these pathogens in the hospital setting is significant health threat. The proposed research will identify (i) transmission risk factors for three of the most prevalent hospital-associated pathogens and (ii) mechanisms that contribute to antibiotic resistance development in bacteria.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
1R01AI143757-01A1
Application #
9972593
Study Section
Genomics, Computational Biology and Technology Study Section (GCAT)
Program Officer
Ritchie, Alec
Project Start
2020-04-03
Project End
2024-03-31
Budget Start
2020-04-03
Budget End
2021-03-31
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Stanford University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305