Blue Devil Resistome Project (2017-2018)


The World Health Organization ranks antibiotic resistance as one of the top three threats to global health and cites Enterobacteriaceae (e.g., E. coli, Klebsiella, Enterobacter) as Priority 1 for R&D of new antibiotics. Antibiotic pipelines are drying up, and acquisition of resistance appears to be accelerating, making it critical to utilize the antibiotics already on the market more effectively. To do so requires a deeper understanding of the scope of antibiotic resistance in the environment, how different types of antibiotic resistance spread and how to interfere with such spread.

The past several decades have witnessed rapid rise of antibiotic resistance globally. Several southern hospitals, including the Duke hospital, have seen a steady increase in the incidence of bacterial pathogens expressing extended spectrum beta-lactamases. It was also found that the majority of patients acquired these infections from hospitals or healthcare centers. These observations raise a potential safety concern for individuals who work and live around such facilities.

For instance, do we expect a greater prevalence of different bacterial pathogens in the environment near hospitals, healthcare centers or research labs dealing with pathogens? Are these pathogens present at a level to warrant concern or preventive measures? What preventive measures should we take to limit the spread of antibiotic-resistance pathogens or genes?

Project Description

To address these questions, we must first understand what is out in the environment. The Bass Connections Blue Devil Resistome Project will tackle this challenge by mapping the distribution of antibiotic-resistance genes across the Duke campus.

The project will be highly multidisciplinary, engaging researchers and undergraduate and graduate students with backgrounds in biology, engineering, genomics, computational sciences, bioinformatics, global health and policy. The project will provide a concrete context for participating students to conduct research that has direct societal impact, with global implications. This will evolve into a long-term project for research and education.

Research activities include primarily the following aspects:

  1. Sampling and sample processing: The project team will collect environmental samples from selected locations across the Duke campus. These samples will be further processed and analyzed by identifying the presence of different microbial species and antibiotic-resistance genes. Selected samples will be stored for future analysis (e.g., whole genome sequencing).
  2. Geospatial health analysis: The team will develop a sample collection strategy to track sample specimens, environmental conditions and date/time collected. Existing platforms such as the GIS Cloud Mobile Data Collection (MDC) will be evaluated for their suitability for the study. The team will also be responsible for leading the geospatial analysis and will review existing platforms for suitability for this study, such as the Berkeley Image Segmentation Algorithm at BIS Cloud, to characterize campus locations.
  3. Data analysis and development of a database: In parallel, the team will create a database to document the information collected above. As the project proceeds, team members will develop computational tools or software for analyzing and disseminating the data.

The project will allow researchers to develop a better understanding of the potential risks associated with hospitals and healthcare centers, which may be generally relevant to similar facilities elsewhere. It will also allow us to evaluate intervention strategies that can curtail the spread of antibiotic resistance, again applicable beyond Duke. Scientifically, the work will generate a valuable resource for future multidisciplinary research on environmental microbes and infectious diseases.

Anticipated Outcomes

Microbiological samples from various parts of the Duke campus; mapping of these samples to their locations; initial characterization of the prevalence of antibiotic resistance genes in these samples; database for the collected samples and a collection of selected, culturable microbes

Student Opportunities

Students with backgrounds in biology, engineering and computer science are encouraged to apply. Depending on their background, each team member will focus on either the experimental or the computational aspects of the project. However, all students are expected to work together during each phase of the project. The participating undergraduate students will be guided by graduate students and postdocs and will gain expertise in microbiological and/or bioinformatics techniques, including:

  1. Sampling microbes from the environment
  2. Analysis of the microbes using standard techniques in microbiology, molecular biology and genomics
  3. Construction of a database on the sampled microbes.

This project will set a foundation for developing a bio-surveillance at Duke and beyond. Participating students will learn about antibiotic resistance and relevant implications for public health and policy making. Through working in an interdisciplinary team, students will gain hands-on experience in experimental analysis of antibiotic resistance, as well as generation, curation and dissemination of data associated with the analysis of collected biological samples.

To apply, please use this online application. The deadline for priority consideration of applications was April 26, 2017, at 5:00 p.m., but we will still accept applications for a limited time.

The following background materials may be of interest:

  • Thaden et al, Increasing Incidence of Extended-Spectrum β-Lactamase-Producing Escherichia coli in Community Hospitals throughout the Southeastern United States. Infection Control & Hospital Epidemiology, 2016, 1:4
  • Afshinnekoo et al, Geospatial Resolution of Human and Bacterial Diversity with City-Scale Metagenomics, Cell Systems, 2015, 1:72
  • Bik et al, Microbial Community Patterns Associated with Automated Teller Machine Keypads in New York City. mSphere 2016, 1:e00226
  • New York Times article on a research study revealing antibiotic-resistant genes in Beijing smog.


Summer 2017 – Spring 2018

Dates and activities are subject to change based on student schedules.

  • Summer 2017: We expect to recruit three undergraduate students and one graduate student to initiate the project during the summer. We will have weekly team meetings to update project progress and to revise research plan as needed. The focus of the summer period will be on developing robust protocols for sampling, sample analysis, and data documentation. These protocols will be documented in weekly reports, which will be updated/revised as the project proceeds. At the end of the summer, the team will present a joint presentation. These protocols will be the blueprint for the project participants during the fall semester.
  • Fall 2017: Independent study requirements (dates and activities subject to change based on student schedules): September 5, full team meeting (5-7 p.m.), Introductions/Project Overview; September 12, full team meeting (5-7 p.m.), (Continued) Project Overview/Discussion of Team Projects; September 19, students are required to complete training laboratory protocols, which are to be established based on the work in the summer period. Thereafter, the team will meet weekly to update project progress and to address issues that arise during each week. These meetings are tentatively scheduled for Tuesdays or Thursdays, 5-7 p.m. (subject to change based on schedule of participants). At the end of the semester, the team will submit a final project report, which will serve as the foundation for the continuation of the project in the spring.
  • Spring 2018: Independent study requirements will be similar to those for Fall 2017.


Independent study credit available for fall and spring semesters

Additional support for this project is provided by The Snyderman Fund to encourage undergraduate research in the genomics.

Faculty/Staff Team Members

Geoffrey Ginsburg, School of Medicine; Center for Applied Genomics and Precision Medicine
Claudia Gunsch, Pratt - Civil & Environmental Engineering
Susanne Haga, School of Medicine; Sanford School; Center for Applied Genomics and Precision Medicine; Center for Genomic and Compuational Biology
Raphael Valdivia, School of Medicine - Molecular Genetics & Microbiology
Lingchong You, Pratt - Biomedical Engineering*

* denotes team leader


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