Diagnosis of infection is typically based on direct detection of the pathogen and/or its products in bodily fluids and tissues. This approach has limited sensitivity and speed of detection. We propose to develop a novel, host-based diagnostic assay platform for blood-based assays combining: (1) the precision of antigen-specific immune responses, (2) the versatility and robustness of nucleic acid detection by fluorescence in situ hybridization (FISH), and (3) the diagnostic and prognostic power of single-cell analysis by flow cytometry. Our preliminary work shows that stimulation of peripheral blood T lymphocytes ex vivo induces expression of mRNA for key cytokines (IL-2, IFN-? and TNF-?) that is detected by hybridization with gene-specific FISH probes and single- and multi-parameter flow cytometry. We now propose to move this platform through preclinical product development for diagnosis of tuberculosis (TB) in partnership with Oxford Immunotec, a world leader in FDA-approved, host-based TB diagnostics. TB is the selected pathology because: (i) it is a global health problem; (ii) M. tuberculosis infection is diagnosed by detecting antigen- specific T cell responses; and (iii) i has a complex clinical presentation ranging from asymptomatic, latent infection (LTBI) to active pulmonary tuberculosis (PTB). Application of our FISH-Flow platform to TB diagnosis is expected to yield a test with superior diagnostic accuracy and speed than the existing tests. Moreover, the platform has the unparalleled potential to distinguish between LTBI and PTB through its multi-parameter capacity, since stages/progression of infection are associated with different cytokine profiles. We will optimize key assay parameters and verify the resulting standardized assay for protocol robustness and reproducibility, assay duration, and initial assessment of diagnostic accuracy in comparison with an existing FDA-approved test. Future kit manufacturability will also be explored. The first outcome will be a simple and accurate single- cytokine assay for LTBI diagnosis that equals or exceeds the clinical accuracy of the existing LTBI diagnostics and surpasses them in speed and ease of execution. The second outcome will be the evaluation of the three- cytokine readout for distinguishing LTBI from PTB. Established collaborations at the PI site and at Oxford Immunotec with clinical sites in regions with low and high TB prevalence will provide blood samples from donors in all TB diagnostic groups. We have also shown that the FISH-Flow protocol is amenable to adaption to microfluidics-based, automated platforms. A third outcome will be automation of all assay steps upstream of flow-cytometry detection (from sample preparation to nuclei acid staining) to obtain a semi-automated device operating with standard flow cytometry. This work, conducted by our bioengineer partner who is experienced in commercializing diagnostic devices, should eventually lead to a hand-held, fully automated device with sample-in-answer-out capability. The FISH-Flow platform in its manual and automated versions will be applicable to detection of receptor-mediated responses in many infectious and non-infectious pathologies.

Public Health Relevance

Fast, affordable and reliable diagnosis of an infection with the bacteria that cause tuberculosis before a person shows symptoms is critical to eliminating tuberculosis. This collaborative proposal establishes a partnership toward development of a next-generation diagnostic test for tuberculosis between academic investigators and a medical diagnostics company that has already developed FDA-approved tuberculosis diagnostics. The plan is designed to refine and validate a promising diagnostic procedure (assay) that detects the responses of human immune cells to tuberculosis infection, resulting in both manual and semi-automated versions of the assay that will determine whether a person is infected with the bacteria and the stage of that infection.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI104615-05
Application #
9319621
Study Section
Special Emphasis Panel (ZAI1)
Program Officer
Lacourciere, Karen A
Project Start
2013-08-15
Project End
2019-07-31
Budget Start
2017-08-01
Budget End
2019-07-31
Support Year
5
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Rutgers University
Department
Public Health & Prev Medicine
Type
Schools of Medicine
DUNS #
078795851
City
Newark
State
NJ
Country
United States
Zip Code
07103
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