293t-ne-3nrs
293t-ne-3nrs - Related Videos
09:02
Modeling Hepatitis B Virus Infection in Non-Hepatic 293T-NE-3NRs Cells
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Cited by 1 •
2020
This manuscript describes a detailed protocol for Hepatitis B virus (HBV) infection in novel engineered 293T cells (293T-NE-3NRs, expressing human NTCP, HNF4α, RXRα and PPARα) and traditional hepatic cells (HepG2-NE, expressing human NTCP).
09:40
Production of Replication-Defective Retrovirus by Transient Transfection of 293T cells
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Cited by 16 •
2007
This technique demonstrates an efficient way to prepare replication-defective retroviral stocks encoding a human oncogene, and subsequently used for induction of myeloproliferative disease in the mouse model.
09:29
Analysis of Nonhomologous End Joining and Homologous Recombination Efficiency in HEK-293T Cells Using GFP-Based Reporter Systems
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Cited by 1 •
2024
This protocol describes an extrachromosomal nonhomologous end joining (NHEJ) assay and homologous recombination (HR) assay to quantify the efficiency of NHEJ and HR in HEK-293T cells.
12:59
Optimized Transfection Strategy for Expression and Electrophysiological Recording of Recombinant Voltage-Gated Ion Channels in HEK-293T Cells
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Cited by 23 •
2011
Reliable method for highly efficient in vitro expression and subsequent electrophysiological recording of recombinant voltage-gated ion channels in cultured human embryonic kidney cells (HEK-293T).
09:38
Direct Reprogramming of Mouse Fibroblasts into Melanocytes
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Cited by 2 •
2021
Here, we describe an optimized direct reprogramming system for melanocytes and a high-efficiency, concentrated virus packaging system that ensures smooth direct reprogramming.
FAQs
The engineered background allows investigators to introduce defined cellular factors or reporter components and examine their effects under reproducible conditions. Because these elements are expressed in the same model context, differences in infection, entry, replication, or immune-response signals can be linked more directly to the factor being tested. This supports controlled dissection of host-pathogen interactions.
A controlled background makes it easier to compare conditions and attribute changes in measured signals to experimental variables. Compared with primary samples, the model reduces biological variability, which can help reveal relationships between a pathogen determinant and a cellular response. This consistency is especially useful when comparing candidate factors or evaluating candidate inhibitors.
Changes in cell-based readouts provide measurable evidence of processes such as pathogen entry, replication, or immune-response signaling. Investigators can relate those changes to introduced cellular factors, reporter components, or pathogen determinants rather than relying only on qualitative observations. The resulting measurements help connect molecular interactions with observable infection phenotypes.
The main distinction is experimental control and biological variability. 293t-ne-3nrs provides a reproducible cellular background in which defined factors or reporters can be introduced, whereas primary samples may show greater variability between biological sources. The engineered model therefore helps isolate specific host-pathogen relationships, while primary samples may provide a different context for confirming biological relevance.
A high-level workflow begins by selecting the model, introducing defined factors or reporter components, allowing their expression, conducting infection or interaction assays, and measuring changes in cell-based readouts. Specific culture conditions, exposure parameters, and detection instruments must be established according to the research question and assay design.
Applications include mechanistic studies of pathogen tropism, evaluation of viral or microbial determinants, and testing of candidate inhibitors. In immunology and infection research, the system helps connect a defined molecular interaction with a measurable infection phenotype or immune-response signal. It is therefore useful for comparing how particular host or pathogen factors influence experimental outcomes.