Biofilms are microbial communities that grow attached to a surface. Biofilm-based infections occur frequently, and biofilm growth on indwelling devices is very difficult to eradicate. Low rates of antibiotic transport within biofilms, protective effects of the biofilm matrix, and low rates of metabolic activity within the biofilm interior have all been found to contribute to the persistence of these infections, but there is currently little understanding of the processes responsible for these effects. While spatial heterogeneity in biofilms is clearly important to selection of therapy for biofilm-based infections, little information is available on the way in which local environmental conditions influence the development of spatial patterns in biofilms, and hence how the effectiveness of antibiotics varies depending on the body site and type of indwelling device. We hypothesize that spatial patterns of metabolic activity within a biofilm are influenced by spatial patterns in the flow environment, and that these interactions cause biofilm complexity to increase over time. We also hypothesize that the flow environment affects biofilm antimicrobial susceptibility not only by influencing delivery of antimicrobials to cells within the biofilm but also by dictating metabolic gradients within the community. We propose to address these hypotheses through the following specific aims.
Aim 1 : Observe growth of mono- species biofilms in a planar flow cell in order to assess changes in biofilm morphology, transport patterns, and metabolic activity with increasing spatial variability in environmental flow conditions.
Aim 2 : Observe the effectiveness of antibiotic treatment in eradicating biofilms having different degrees of spatial complexity, and relate the distribution of local killing efficiency to spatial patterns in transport conditions and metabolic activity.
Aim 3 : Develop an improved numerical model to allow quantitative analysis of the effects described above.
Aim 4 : Use the model to clarify multi-scale flow-biofilm interactions, and particularly to evaluate the key features that contribute to the survival of subpopulations of cells in biofilms under antibiotic treatment. We propose to achieve these aims by using a combination of novel experiments and numerical modeling. We will conduct experiments on biofilm growth and treatment in a new experimental system that provides the ability to impose a precisely controlled degree of spatial variability in inflow and outflow patterns. Biofilm growth, changes in flow and oxygen distributions, transport of antibiotic, and the resulting cell death will all be observed directly in situ. We will utilize these new and unique observations to support development of a new numerical model for biofilm development, which will subsequently be used to simulate the effectiveness of antibiotic treatment in eradicating biofilms under different local growth conditions. This combination of measurements and modeling will provide unique insight into the way in which biofilm growth interacts with and modifies the external flow, and ultimately how this complex interaction controls the overall formation of the biofilm and the effects of introduced antimicrobial agents on cells residing in the biofilm matrix.

Public Health Relevance

Metabolic heterogeneity and antibiotic susceptibility in biofilms Summary Narrative Biofilm-based infections of inserted and implanted medical devices such as catheters, neurosurgical devices, and orthopedic devices are difficult to treat. Low rates of antibiotic transport within biofilms, protective effects of the biofilm matrix, and low rates of metabolic activity within the biofilm interior have all been found to contribute to the persistence of these infections, but there is currently little understanding of the processes responsible for these effects. The proposed work will advance understanding of how local environmental conditions influence biofilm growth, and will develop improved tools for assessing the effectiveness of antibiotics against biofilm-based infections.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI081983-03
Application #
8318234
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Gezmu, Misrak
Project Start
2010-09-07
Project End
2015-08-31
Budget Start
2012-09-01
Budget End
2013-08-31
Support Year
3
Fiscal Year
2012
Total Cost
$367,133
Indirect Cost
$81,567
Name
Northwestern University at Chicago
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
160079455
City
Evanston
State
IL
Country
United States
Zip Code
60201
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