Poster L4 - Decellularization Dynamics: A Mathematical Approach to DNA Quantification in Soft Tissue Decellularization

Thursday, October 24, 2024

10:00 AM - 11:00 AM EST

Location: Exhibit Hall E, F & G

Presenting Author(s)

Shivani Gera (she/her/hers)

Student
Joint Department of Biomedical Engineering, North Carolina State and University of North Carolina-Chapel Hill, Raleigh, NC, United States of America
Raleigh, North Carolina, United States

Co-Author(s)

Chloe Hincher

Graduate Student
Joint Department of Biomedical Engineering, North Carolina State and University of North Carolina-Chapel Hill, Raleigh, NC, United States of America
Raleigh, North Carolina, United States
SW

Shelby White

Post-Doc
Joint Department of Biomedical Engineering, North Carolina State and University of North Carolina-Chapel Hill, Raleigh, NC, United States of America, United States

Primary Investigator(s)

Donald Freytes

Associate Professor
Joint Department of Biomedical Engineering, North Carolina State and University of North Carolina-Chapel Hill, Raleigh, NC, United States of America, United States

Co-Author(s)

Camilo Mora Navarrro, PhD (he/him/his)

Associate Professor
University of Puerto Rico
MAYAGUEZ, Puerto Rico, United States
DS

Daphne Sze

Graduate Student
Joint Department of Biomedical Engineering, North Carolina State and University of North Carolina-Chapel Hill, Raleigh, NC, United States of America, United States

Introduction: The extracellular matrix (ECM) is a multifaceted and dynamic mesh of macromolecules that fills the extracellular space within tissues. The composition and organization of these macromolecules differ based on the tissue type, contributing to each tissue's distinct mechanical properties by creating an interconnected and stable framework. The ECM is vital for various functions in the human body, such as providing structural support, promoting cell adhesion, regulating cellular activities, and assisting in tissue repair. Furthermore, the ECM is essential for tissue regeneration, constantly undergoing remodeling through synthesis and degradation to adjust to physiological changes and environmental signals. Decellularization primarily removes native cells and genetic materials, such as DNA, from the ECM while preserving its biochemical and biomechanical properties. Decellularized ECM has been successfully employed to recreate a variety of tissues and organs. However, the ECM manufacturing method through decellularization, which removes immunogenic factors like DNA to avert host rejection, is currently poorly standardized across laboratories, presenting significant challenges in terms of cost and development timelines in the field. This study aims to determine a mathematical model for the decellularization process. This will be done by quantifying the DNA concentration at various steps of the decellularization process and ultimately correlating the values mathematically. We hypothesized that mathematical models can be applied to monitoring cell signals and allow us to better predict and determine the efficacy of decellularization.

Materials and

Methods: Porcine lung dissections were performed, and nine independent decellularizations were carried out. Porcine lungs were dissected and cleaned to remove excess connective tissue, blood, and clots. The tissue was cut into small pieces, placed between acrylic plates, and secured by binder clips. These pieces were frozen at -80C for ~ 30 minutes, and then a tissue chopper was used to cut the tissue into smaller pieces. For the manual decellularization process, 1 gram of tissue was weighed for each decellularization, placed in a 100-um filter, and centrifuged at 3000 rpm for 30 seconds to remove excess blood and water. The tissue was placed in 50 mL tubes and treated with a series of reagents, as shown in Table 1.
The decellularization was stopped at different steps: 4% Sodium Deoxycholate (SDC), DNAse I, and 0.1% Peracetic Acid. Triplicates were made for each sample step (i.e. 3 decellularization each for SDC, DNAse, and Peracetic Acid). Nanodrop readings were taken every 10 minutes while the samples were in each reagent. Once the decellularization process was stopped at each respective step, the samples were frozen overnight at -20C, powdered the following day, and lyophilized for 24 hours. The initial wet weight and final weight after lyophilization were noted and correlated. PicoGreen DNA quantification was performed for each sample, and the data was analyzed.

Results, Conclusions, and Discussions:

Results:
The PicoGreen readings were taken for each sample and indicated a substantial reduction in the amount of DNA in the subsequent steps of the decellularization process. SDC readings showed DNA concentrations similar to those of the native sample. However, there was a reduction in DNA concentration after the DNAse, and these results were similar to those of Peracetic Acid. These values were then correlated with the tissue weights after decellularization at the SDC, DNAse, and Peracetic Acid steps, and a mathematical model was established.

Conclusions:
We established a preliminary mathematical model for the manual decellularization process. This determined the concentration of DNA at the SDC, DNAse, and Peracetic Acid steps of the process. Although this study only used porcine lung tissue for decellularization, using different types of tissue and correlating the data could give a more accurate mathematical model. Creating such models and understanding the kinetics of decellularization is key for integrating tissue engineering and regenerative medicine benchtop strategies into clinical and industrially focused applications.

Discussion:
This study aimed to determine a mathematical model that would allow us to quantify the concentration of DNA at the SDC, DNAse, and Peracetic Acid steps of the process while taking into account the fact that the mass changes at every step. It was determined that the maximum amount of DNA was removed during the DNAse step, which correlates with the PicoGreen analysis and nanodrop readings. However, this study has limitations. Prolonged exposure to strong decellularization reagents may impact key structural proteins. While structural changes (i.e.histology) were outside the scope of this preliminary study, future work should carefully consider impacts on the structural integrity of ECM components. Additionally, incorporating a variety of tissues for decellularization could yield a more accurate mathematical model.

Acknowledgements (Optional):