Rapid, efficient differential diagnosis is critical to controlling the morbidity and mortality of acute infectious diseases and to enabling efficient resource allocation. Many infectious diseases present with non-specific signs and symptoms; hence, history and physical exam alone are typically insufficient to inform clinical management or characterize outbreaks. A wide range of molecular methods have been developed for direct detection of microbial nucleic acids in clinical materials. These advances have transformed microbiology and medicine; nonetheless, high throughput sequencing, the most highly multiplexed of these methods, remains too complex and expensive for application in many clinical settings. Furthermore, none of these methods will serve in instances where microbial nucleic acids are not present in an accessible sample or where disease may have been triggered by an agent that is no longer present. The risk of developing disease and its severity after exposure to an infectious agent is modulated by an individual's previous exposures to similar agents or vaccines. Such exposures may confer complete or partial protection or result in increased risk for more severe disease due to antibody-mediated enhancement, as is the case in dengue fever. Thus, knowledge of an individual's immunological history may influence decisions concerning his/her treatment, vaccination or deployment as a first responder or health care worker in areas with increased probability of encountering specific pathogens. Our objective is to enhance differential diagnosis and management of infectious diseases through pursuit of two aims that will (1) establish a new highly multiplexed serology platform for profiling a subject's pathogen exposure history and (2) improve the efficiency of sequencing for direct detection of microbial nucleic acids in clinical specimens. Investments in sequencing have largely focused on driving down costs per base and on increasing read length and number. We will complement these efforts by establishing new methods for sample preparation that will enrich for relevant template, thereby enhancing efficiency and reducing the complexity of bioinformatic analyses.

Public Health Relevance

This project will reduce the morbidity, mortality and economic cost of infectious diseases by providing new tools for diagnosis and discovery of infectious agents, as well as detecting evidence of exposure.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program--Cooperative Agreements (U19)
Project #
5U19AI109761-04
Application #
9241960
Study Section
Special Emphasis Panel (ZAI1)
Project Start
2017-03-01
Project End
2019-02-28
Budget Start
2017-03-01
Budget End
2018-02-28
Support Year
4
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Columbia University (N.Y.)
Department
Type
DUNS #
621889815
City
New York
State
NY
Country
United States
Zip Code
10032
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