Optimized protocol for gene editing in adipocytes using CRISPR-Cas9 technology

3D culture induction of adipogenic differentiation in 3T3-L1 preadipocytes exhibits adipocyte-specific molecular expression patterns and metabolic functions

Adipose tissues are closely related to physiological functions and pathological conditions in most organs. Although differentiated 3T3-L1 preadipocytes have been used for in vitro adipose studies, the difference in cellular characteristics of adipogenic differentiation in two-dimensional (2D) culture and three-dimensional (3D) culture remain unclear. In this study, we evaluated gene expression patterns using RNA sequencing and metabolic functions using an extracellular flux analyzer in 3T3-L1 preadipocytes with and without adipogenic induction in 2D culture and 3D culture. In 2D culture, 565 up-regulated genes and 391 down-regulated genes were identified as differentially expressed genes (DEGs) by adipogenic induction of 3T3-L1 preadipocytes, whereas only 69 up-regulated genes and 59 down-regulated genes were identified as DEGs in 3D culture. Ingenuity Pathway Analysis (IPA) revealed that genes associated with lipid metabolism were identified as 2 out of the top 3 causal networks related to diseases and function in 3D spheroids, whereas only one network related to lipid metabolism was identified within the top 9 of these causal networks in the 2D planar cells, suggesting that adipogenic induction in the 3D culture condition exhibits a more adipocyte-specific gene expression pattern in 3T3-L1 preadipocytes. Real-time metabolic analysis revealed that the metabolic capacity shifted from glycolysis to mitochondrial respiration in differentiated 3T3-L1 cells in the 3D culture condition but not in those in the 2D cultured condition, suggesting that adipogenic differentiation in 3D culture induces a metabolic phenotype of well-differentiated adipocytes. Consistently, expression levels of mitochondria-encoded genes including mt-Nd6, mt-Cytb, and mt-Co1 were significantly increased by adipogenic induction of 3T3-L1 preadipocytes in 3D culture compared with those in 2D culture. Taken together, the findings suggest that induction of adipogenesis in 3D culture provides a more adipocyte-specific gene expression pattern and enhances mitochondrial respiration, resulting in more adipocyte-like cellular properties.

Optimized protocols for efficient gene editing in mouse hepatocytes in vivo using CRISPR-Cas9 technology

We provide a protocol for gene editing in mouse hepatocytes in vivo using the CRISPR-Cas9 technology via AAV delivery. This protocol describes the construction of AAV plasmids, AAV packaging, injection, and the detection of in vivo knockout efficiency. Using this protocol, we can get up to 10¹⁴ AAV and knock out genes in hepatocytes efficiently within 15 days. Moreover, we describe an optimized protocol to simultaneously target two genes via AAV delivery of CRISPR-Cas9 materials in the liver.

For complete details on the use and execution of this profile, please refer to Wei et al. (2020).

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Gene editing in hepatocytes in vivo using CRISPR-Cas9 technology

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Dual gene editing in vivo using optimized protocol

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High titer of AAV can be produced using this protocol

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Multiple techniques to detect AAV infection efficiency

A proteomics protocol to identify stimulation-induced binding partners dependent on a specific gene in mammalian cells

Some protein-protein interactions are induced by different kinds of stimulation and are dependent on specific genes. To identify these interaction partners, we present a protocol which utilizes affinity purification of Flag-tagged protein complexes followed by mass-spectrometry-based proteomics to compare stimulation-induced interactomes between wild-type and CRISPR-Cas9-mediated knockout cells. The candidates of interest are identified using bioinformatic analyses and verified by biochemical approaches. This protocol is highly versatile and applies to a variety of cells and different types of stimulation.

For complete details on the use and execution of this protocol, please refer to (Zhu et al., 2021).

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Protocol for identifying stimulation-dependent protein-protein interaction

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Protocol for identifying a specific gene-dependent interactome

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The protocol applies to a variety of cells and different types of stimulation

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Bioinformatic and biochemical analyses can help to exclude non-specific interactions