Ms. Jennifer M. Knighten Profile

Jennifer M. Knighten

at Univ of South Alabama

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Publications (2)

Proceedings Article | 15 March 2023 Presentation + Paper

Combined hyperspectral imaging, monolayer stress microscopy, and S8 image analysis approaches for simultaneously interrogating cellular signals and biomechanics

Silas Leavesley, Santina Johnson, Sunita Paudel, Jennifer Knighten, Dhananjay Tambe, Michael Francis, Na Gong, Mark Taylor, Thomas Rich

Proceedings Volume 12383, 123830D (2023) https://doi.org/10.1117/12.2650653

KEYWORDS: Hyperspectral imaging, Image analysis, Calcium, Monolayers, Microscopy, Hydrogels, Microspheres, Image visualization, Visualization, Statistical analysis, Fluorescence, Signaling molecules

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Second messenger signals, e.g., Ca²⁺ and cyclic nucleotides, orchestrate a wide range of cellular events. The methods by which second messenger signals determine specific physiological responses are complex. Recent studies point to the importance of temporal and spatial encoding in determining signal specificity. Studies also indicate the importance of mechanical stimuli, substrate stiffness, and mechanical responses–the “mechanosome”–in regulating physiology. Hence, approaches that probe both chemical and mechanical signals are needed. Here, we report preliminary efforts to combine hyperspectral imaging for second messenger signal measurements, monolayer stress microscopy for mechanical force measurements, and S8 analysis software for quantifying localized signals–specifically, Ca²⁺ dynamics and mechanical forces in human airway smooth muscle cells (HASMCs). HASMCs were prepared as confluent monolayers on 11 kPa gels with embedded fluorescent microparticles that serve as fiducial markers as well as smaller microparticles to measure deformation (strain). Imaging was performed using a custom excitation-scanning hyperspectral microscope. Hyperspectral images were unmixed to identify signals from cellular fluorescent labels (e.g., CAL 590-AM) and fluorescent microparticles. Images were analyzed to quantify localized force dynamics through monolayer stress microscopy. S8 software was used to identify, track, and quantify spatially-localized Ca²⁺ activity. Results indicate that localized and transient cellular signals and forces can be quantified and mapped within cell populations. Importantly, these results establish a method for simultaneous interrogation of cellular signals and mechanical forces that may play synergistic roles in regulating downstream cellular physiology in confluent monolayers. This work was supported by NIH P01HL066299, R01HL137030, R01HL058506, and NSF MRI1725937. Drs. Leavesley and Rich disclose financial interest in a university start-up company, SpectraCyte LLC, to commercialize spectral imaging technologies.

Proceedings Article | 15 March 2023 Presentation + Paper

Dynamic region of interest histometric analysis of endogenous calcium activity in intact lung tissue

Pallavi Sen, Jennifer Knighten, Takreem Aziz, Christian Macarilla, Na Gong, Mark Taylor, C. Michael Francis

Proceedings Volume 12383, 123830A (2023) https://doi.org/10.1117/12.2650410

KEYWORDS: Calcium, Lung, Signal detection, Tissues, Detection and tracking algorithms, Image filtering, Histograms, Algorithm development, Particles, Signal processing

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Calcium (Ca²⁺) signaling in endothelial cells plays an important role in regulation of wide range of physiological processes in the pulmonary microcirculation. A dysregulation in the intracellular Ca²⁺ concentration can serve as an initiator of different pathological conditions like lung endothelial barrier disruption, edema, inflammation, etc. Normal physiologic signaling is localized spatio-temporally and signaling ‘signatures’ define the specificity of outcomes within the cells. However, analyzing the signaling dynamics acquired through imaging of live tissues has been challenging owing to the intricate patterns of the distinct signals. Moreover, signal analysis tools based on whole-field or static region of interest (ROI) assessments may under- or over-estimate measurements of signaling parameters with respect to event origination, spread and duration. In the current study we designed an algorithm for detection and analysis of these biological signaling events based on dynamic ROI tracking, where time-dependent polygonal ROIs are automatically assigned to the changing perimeters of detected signaling events. This approach allowed for robust tracking of signals and quantification of the signaling event parameters over time. We next applied this algorithm on image sequences of lung slices isolated from genetically encoded mice expressing the endothelial specific cdh5GCaMP8 (GFP-based) calcium indicator, and observed an inherent dynamic Ca²⁺ signaling profile within the pulmonary microvascular endothelium. To investigate the versatility of our algorithm, we further treated the lung slices with acetylcholine (ACh) or subjected them to Ca²⁺-free (CAF) medium, to examine the emerging change in patterns of the profiles from the inherent basal dynamics. Under both these conditions, our software revealed distinct changes in event parameters with respect to event amplitude, duration and spread of the signaling events. Thus, our algorithm allowed us to identify distinct Ca²⁺ signaling patterns associated with various stimuli, thereby enabling identification of these signatures under a wide variety of sub-cellular/pathologic challenges.

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