Multiscale modeling of HBV infection integrating intra- and intercellular viral propagation for analyzing extracellular viral markers

• Published in: bioRxiv
• Main Authors: Kitagawa, Kosaku, Kim, Kwang Su, Iwamoto, Masashi, Hayashi, Sanae, Park, Hyeongki, Nishiyama, Takara, Nakamura, Naotoshi, Fujita, Yasuhisa, Nakaoka, Shinji, Aihara, Kazuyuki, Perelson, Alan S, Allweiss, Lena, Dandri, Maura, Watashi, Koichi, Tanaka, Yasuhito, Iwami, Shingo
• Format: Journal Article Paper
• Language: English
• Published: United States Cold Spring Harbor Laboratory 07.06.2023
• Edition: 1.1
• Subjects: Microbiology
• ISSN: 2692-8205; 2692-8205
• DOI: 10.1101/2023.06.06.543822

Chronic infection of hepatitis B virus (HBV) is caused by the persistence of closed circular DNA (cccDNA) in the nucleus of infected hepatocytes. Despite available therapeutic anti-HBV agents, eliminating the cccDNA remains challenging. The quantifying and understanding dynamics of cccDNA are essential for developing effective treatment strategies and new drugs. However, it requires a liver biopsy to measure the intrahepatic cccDNA, which is basically not accepted because of the ethical aspect. We here aimed to develop a non-invasive method for quantifying cccDNA in the liver using surrogate markers present in peripheral blood. We constructed a multiscale mathematical model that explicitly incorporates both intracellular and intercellular HBV infection processes. The model, based on age-structured partial differential equations (PDEs), integrates experimental data from in vitro and in vivo investigations. By applying this model, we successfully predicted the amount and dynamics of intrahepatic cccDNA using specific viral markers in serum samples, including HBV DNA, HBsAg, HBeAg, and HBcrAg. Our study represents a significant step towards advancing the understanding of chronic HBV infection. The non-invasive quantification of cccDNA using our proposed methodology holds promise for improving clinical analyses and treatment strategies. By comprehensively describing the interactions of all components involved in HBV infection, our multiscale mathematical model provides a valuable framework for further research and the development of targeted interventions.