Correlated chemical imaging is an emerging strategy for acquisition of images by combining information from multiplexed measurement platforms to track, visualize, and interpret in situ changes in the structure, organization, and activities of interesting chemical systems, frequently spanning multiple decades in space and time. Acquiring and correlating information from complementary imaging experiments has the potential to expose complex chemical behavior in ways that are simply not available from single methods applied in isolation, thereby greatly amplifying the information gathering power of imaging experiments. However, in order to correlate image information across platforms, a number of issues must be addressed. First, signals are obtained from disparate experiments with fundamentally different figures of merit, including pixel size, spatial resolution, dynamic range and acquisition rates. In addition, images are often acquired on different instruments in different locations, so the sample must be registered spatially so that the same area of the sample landscape is addressed. The signals acquired must be correlated in both spatial and temporal domains, and the resulting information has to be presented in a way that is readily understood. These requirements pose special challenges for image cross-correlation that go well beyond those posed in single technique imaging approaches.
The work described in this thesis focuses on employing molecular imaging to study complex samples, in particular biological samples that exhibit great complexities in their chemical species and often tend to be dynamic, thus making it difficult to perform imaging and chemical analysis using one technique. The work demonstrates the utility of combining complementary experiments to perform chemical imaging. Specifically, a correlated imaging platform combining mass spectrometry techniques is developed to overcome technical limitations in each method and to amplify the information gathering power in the experiments. The work describes the designing and implementation of the imaging platform and shows its utility in studying bacterial biofilms.