Bacterial infections impose a costly health burden worldwide which is compounded by the alarming increase of multi-drug resistant bacteria, and many of these infections are in the urogenital tract. Urogenital tract infections (UTI) afflict mor than 250 million adults and children worldwide each year. However, pharmaceutical companies tasked with developing the next class of antibiotics do not have the tools to monitor in vivo bacterial organ burden quantitatively and longitudinally in the same small animal without harvesting organs. Consequently, the life cycle of pathogenic bacteria and the efficacy of novel antibiotics cannot be studied in real-time. Luminescent bacteria are commonly used as a tool for optical imaging of in vivo bacterial infections in small animals, however, light is strongly attenuated by tissue and the measured signal is dependent on (i) the spatial location of bacteria, (ii) the heterogeneous optical tissue properties, and (iii) the animal's size and shape. There is currently no commercial tool that effectively addresses these burdens for accurate in vivo quantification and localization of the bacterial density distribution inside tissue. Therefore, the proposed work is aimed at developing an integrated hardware and software unit for optical imaging systems that (i) will directly calculate the bacterial burden in a living animal and (ii) instantaneously co-register it to the animal's anatomy. This task will be accomplished through a novel in vitro optical calibrator, a body-shape-conforming animal mold, and a digital mouse atlas. The calibrator mimics optical tissue properties and, thus, will enable the quantification of the bacterial light yield. The optically transparent and body-shape-conforming animal mold provides a fixed geometry for the animal while enabling (i) the co-registration to the digital mouse atlas and (ii) the construction of a heterogeneous optical property map for a light propagation model.
In Aim 1, a novel digital mouse atlas based on an Organ Probability Map (OPM) will be developed to determine the accurate in vivo anatomical location of bacterial infection.
In Aim 2, the in vivo bacterial density (colony forming units per tissue volume) will be determined in an animal model of urinary tract infection. The proposed imaging unit will (i) shorten in vivo studies by allowing real-time monitoring of bacterial infections in the same animal longitudinally, (ii) provide an instantaneous anatomical reference, and (iii) lower the cost barrier for researchers needing both optical reporter imaging and an anatomical reference without using an additional and expensive anatomical imaging modality like magnetic resonance imaging (MRI). The successful completion of the proposed project will help to commercialize the imaging unit and will find immediate application in the pharmaceutical industry for rapid development of novel antibiotics. The long-term goal is to extend the unit's utility to a number of other fields needing to quantify bioluminescent targets such as in neurobiology, oncology, and stem cell research.

Public Health Relevance

In this Phase I SBIR, InVivo Analytics seeks funding for the development of a new device to monitor animal models of infection in real time. Despite its prevalence, bacterial infections, particularly of the urinary tract, are a significant burden on th health care system because of the lack of new antibiotics being developed. InVivo Analytics will develop a new kind of imaging tool, which can quantify bacterial infection in the living animal, thereby allowing accurate development of novel antibiotics.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Small Business Innovation Research Grants (SBIR) - Phase I (R43)
Project #
1R43EB018644-01A1
Application #
8832227
Study Section
Special Emphasis Panel ()
Program Officer
Conroy, Richard
Project Start
2014-09-30
Project End
2015-06-30
Budget Start
2014-09-30
Budget End
2015-06-30
Support Year
1
Fiscal Year
2014
Total Cost
$214,846
Indirect Cost
Name
In Vivo Analytics, Inc.
Department
Type
DUNS #
009795679
City
New York
State
NY
Country
United States
Zip Code
10033