Conditional cell reprogramming for modeling host‐virus interactions and human viral diseases

Abstract

Conventional cancer and transformed cell lines are widely used in cancer biology and other fields within biology. These cells usually have abnormalities from the original tumor itself, but may also develop abnormalities due to genetic manipulation, or genetic and epigenetic changes during long-term passages. Primary cultures may maintain lineage functions as the original tissue types, yet they have a very limited life span or population doubling time because of the nature of cellular senescence. Primary cultures usually have very low yields, and the high variability from any original tissue specimens, largely limiting their applications in research. Animal models are often used for studies of virus infections, disease modeling, development of antiviral drugs, and vaccines. Human viruses often need a series of passages in vivo to adapt to the host environment because of variable receptors on the cell surface and may have intracellular restrictions from the cell types or host species. Here, we describe a long-term cell culture system, conditionally reprogrammed cells (CRCs), and its applications in modeling human viral diseases and drug discovery. Using feeder layer coculture in presence of Y-27632 (conditional reprogramming, CR), CRCs can be obtained and rapidly propagated from surgical specimens, core or needle biopsies, and other minimally invasive or noninvasive specimens, for example, nasal cavity brushing. CRCs preserve their lineage functions and provide biologically relevant and physiological conditions, which are suitable for studies of viral entry and replication, innate immune responses of host cells, and discovery of antiviral drugs. In this review, we summarize the applications of CR technology in modeling host-virus interactions and human viral diseases including severe acute respiratory syndrome coronavirus-2 and coronavirus disease-2019, and antiviral discovery.

Serially passaged, conditionally reprogrammed nasal epithelial cells as a model to study epithelial functions and SARS-CoV-2 infection

“…It was recently proposed that crNECs could constitute a suitable model to study infection with SARS-CoV-2 coronavirus- and infection-related host responses to identify novel therapeutic targets ( 36 , 48 ). To assess the susceptibility of crNEC epithelia to SARS-CoV-2 infection, we measured expression levels of the primary viral receptor ACE2 ( 49 ) and the serine protease TMPRSS2 , which is important for efficient virus entry ( 50 ).…”

“…Epithelia derived from cr cells have been used previously as ex vivo models to study viral infections ( 48 ). For instance, ALI cultures of AECs developed antiviral response to rhinovirus infection ( 65 ) and were infectible with adenovirus ( 66 ).…”

“…For instance, ALI cultures of AECs developed antiviral response to rhinovirus infection ( 65 ) and were infectible with adenovirus ( 66 ). Accordingly, crNECs were discussed as an appropriate model to study SARS-CoV-2 infection ( 48 ). SARS-CoV-2 infects human epithelia, and high virus levels have been detected in the upper airways ( 67 ).…”

Identification of HPV oncogene and host cell differentiation associated cellular heterogeneity in cervical cancer via single‐cell transcriptomic analysis

“…Lastly, precise processes of HPV life cycle and oncogenesis still remain largely unknown due to the lack of natural systems for HPV productive and abortive life cycles. It would be important to generate more patient‐derived clinically relevant cell models 37,41,42,72 …”

Modeling Human Viral Diseases: Trials and Triumphs

“…However, the availability of larger animals (both inbreed and out breed), cost and ethical concerns pushed the field to identify alternate model systems to study virushost interactions. More recently, 2D cell culture and 3D organoid models have become increasingly prominent and refined disease models for dissecting the molecular mechanisms underlying viral induced pathogenesis (14)(15)(16)(17). Each model has strengths and weaknesses and understanding how these relate to disease phenotypes is key to interpreting the results obtained from these systems.…”