S'identifier

University of South Alabama

7 ARTICLES PUBLISHED IN JoVE

Biology

Automated Analysis of Dynamic Ca²⁺ Signals in Image Sequences

Michael Francis¹, Josh Waldrup², Xun Qian², Mark S. Taylor²

¹Department of Pharmacology, University of South Alabama, ²Department of Physiology, University of South Alabama

Here a novel region of interest analysis protocol based on sorting best-fit ellipses assigned to regions of positive signal within two-dimensional time lapse image sequences is demonstrated. This algorithm may enable investigators to comprehensively analyze physiological Ca²⁺ signals with minimal user input and bias.

Developmental Biology

Reprogramming Primary Amniotic Fluid and Membrane Cells to Pluripotency in Xeno-free Conditions

Jaroslav Slamecka¹, Javier Laurini², Troy Shirley¹, Simon Philipp Hoerstrup³, Benedikt Weber^3,4,5, Laurie Owen¹, Steven McClellan¹

¹Mitchell Cancer Institute, University of South Alabama, ²College of Medicine, University of South Alabama, ³Institute for Regenerative Medicine, University of Zurich, ⁴Department of Dermatology, University Hospital Zurich, ⁵Center for Applied Biotechnology and Molecular Medicine (CABMM), University of Zurich - Irchel Campus

This protocol describes the reprogramming of primary amniotic fluid and membrane mesenchymal stem cells into induced pluripotent stem cells using a non-integrating episomal approach in fully chemically defined conditions. Procedures of extraction, culture, reprogramming, and characterization of the resulting induced pluripotent stem cells by stringent methods are detailed.

Immunology and Infection

Methods for Detecting Cytotoxic Amyloids Following Infection of Pulmonary Endothelial Cells by Pseudomonas aeruginosa

Ron Balczon^1,4, Michael Francis^2,4, Silas Leavesley^3,4, Troy Stevens^2,4

¹Department of Biochemistry and Molecular Biology, University of South Alabama, ²Department of Physiology and Cell Biology, University of South Alabama, ³Department of Chemical and Biomolecular Engineering, University of South Alabama, ⁴Center for Lung Biology, University of South Alabama

Simple methods are described for demonstrating the production of cytotoxic amyloids following infection of pulmonary endothelium by Pseudomonas aeruginosa.

Engineering

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

Joshua Deal^1,2,3, Andrea Britain^2,3, Thomas Rich^2,3, Silas Leavesley^1,2,3

¹Department of Chemical and Biomolecular Engineering, University of South Alabama, ²Center for Lung Biology, University of South Alabama, ³Department of Pharmacology, University of South Alabama

Spectral imaging has become a reliable solution for identification and separation of multiple fluorescence signals in a single sample and can readily distinguish signals of interest from background or autofluorescence. Excitation-scanning hyperspectral imaging improves on this technique by decreasing the necessary image acquisition time while simultaneously increasing the signal-to-noise ratio.

Biology

Measurement of 3-Dimensional cAMP Distributions in Living Cells using 4-Dimensional (x, y, z, and λ) Hyperspectral FRET Imaging and Analysis

Naga S. Annamdevula^1,2, Rachel Sweat³, Hayden Gunn¹, John R. Griswold³, Andrea L. Britain^1,2, Thomas C. Rich^1,2, Silas J. Leavesley^1,2,3

¹Department of Pharmacology, University of South Alabama, ²Center for Lung Biology, University of South Alabama, ³Department of Chemical and Biomolecular Engineering, University of South Alabama

Due to inherent low signal-to-noise ratio (SNR) of Fӧrster resonance energy transfer (FRET) based sensors, measurement of cAMP signals has been challenging, especially in three spatial dimensions. Here, we describe a hyperspectral FRET imaging and analysis methodology that allows measurement of cAMP distribution in three spatial dimensions.

Biology

Integrative Toolkit to Analyze Cellular Signals: Forces, Motion, Morphology, and Fluorescence

Alyson Nguyen^*1, Keith Battle^*2,3, Sunita S. Paudel^*2,3, Ningyong Xu², Jessica Bell³, Linn Ayers³, Cassandra Chapman⁴, Ajay P. Singh⁵, Srinivas Palanki⁶, Thomas Rich^3,7, Diego F. Alvarez⁸, Troy Stevens^2,3, Dhananjay T. Tambe^3,4,7

¹Biomedical Sciences, Pat Capps Covey College of Allied Health Professions, University of South Alabama, ²Department of Physiology and Cell Biology, College of Medicine, University of South Alabama, ³Center for Lung Biology, College of Medicine, University of South Alabama, ⁴William B. Burnsed Jr. Mechanical, Aerospace, and Biomedical Engineering Department, College of Engineering, University of South Alabama, ⁵Mitchell Cancer Institute, College of Medicine, University of South Alabama, ⁶Department of Chemical and Biomedical Engineering, West Virginia University, ⁷Department of Pharmacology, College of Medicine, University of South Alabama, ⁸Department of Physiology & Pharmacology, College of Osteopathic Medicine, Sam Houston State University

The Integrative Toolkit to Analyze Cellular Signals (iTACS) platform automates the process of simultaneously measuring a wide variety of chemical and mechanical signals in adherent cells. iTACS is designed to facilitate community-driven development and enable researchers to use all platform features regardless of their educational background.

Biology

Design and Implementation of a Rat Ex Vivo Lung Perfusion Model

William J. Cleveland^*1, Josephine E. Hees^*1,2, Claudius Balzer^1,2, Hunter F. Douglas¹, Troy Stevens^3,4,5, Matthias L. Riess^1,6,7

¹Anesthesiology, Vanderbilt University Medical Center, ²Anesthesiology, University of Greifswald, ³Department of Physiology and Cell Biology, University of South Alabama, ⁴Department of Medicine, University of South Alabama, ⁵Center for Lung Biology, University of South Alabama, ⁶Anesthesiology, Tennessee Valley Healthcare System Veterans Affairs Medical Center, ⁷Pharmacology, Vanderbilt University

Ex vivo lungs are useful for a variety of experiments to collect physiological data while excluding the confounding variables of in vivo experiments. Commercial setups are often expensive and limited in the types of data they can collect. We describe a method for building a fully modular setup, adaptable for various study designs.