DGAT2 is one of two enzymes that catalyzes the final and only committed step in triacylglycerol (TAG) synthesis. Specifically, DGAT2 catalyzes the reaction in which diacylglycerol is covalently bound to long chain fatty acyl-CoAs to form triglycerides. This reaction is crucial for energy storage in the form of lipid droplets within cells. DGAT2 functions optimally at low concentrations of magnesium chloride, which distinguishes it from DGAT1 that exhibits high activity at elevated magnesium chloride concentrations . Studies in murine models have demonstrated that DGAT2 is responsible for the majority of TAG synthesis in mammalian systems, as DGAT2 knockout mice showed almost no TAG content and died shortly after birth, while DGAT1-deficient mice remained viable with only modest reductions in tissue TG content .
The human DGAT2 gene is located on chromosome 11. The gene encodes multiple transcript variants that result in different isoforms of the DGAT2 protein . These transcript variations contribute to the functional diversity of DGAT2 across different tissues and under different physiological conditions. The gene contains both coding regions (exons) and non-coding regions (introns), with most reported mutations occurring within intronic regions, substitution/missense mutations, and synonymous mutations .
DGAT2 is a transmembrane protein with two predicted transmembrane domains that are critical for its localization and function. Research has identified specific regions that are essential for:
Enzyme catalytic activity: The catalytic site contains conserved residues, with mutations in this region often showing high pathogenicity scores in disease contexts .
Protein-protein interactions: DGAT2 forms multimeric complexes through interactions between individual DGAT2 subunits. Both N-terminal and C-terminal domains mediate these subunit interactions .
Subcellular localization: The first transmembrane domain (TMD1) contains the ER targeting signal, which is essential for proper localization. Without its transmembrane domains, DGAT2 relocates from the ER to mitochondria .
Lipid droplet association: DGAT2 has the ability to associate with lipid droplets even when not localized to the ER, suggesting independent lipid droplet targeting mechanisms .
Despite catalyzing the same chemical reaction, DGAT1 and DGAT2 play distinct roles in triglyceride metabolism:
| Characteristic | DGAT1 | DGAT2 |
|---|---|---|
| Impact on TG synthesis | Modest contribution | Major contributor |
| Knockout phenotype | Viable mice with modest TG reduction | Lethal with almost no TG present |
| Overexpression effect | Moderate increase in intracellular TG | Large increase in intracellular TG |
| Mg²⁺ requirement | High activity at high Mg²⁺ concentrations | Active at low Mg²⁺ concentrations |
| Subcellular localization | Primarily ER | ER, mitochondria, and lipid droplets |
The significantly more severe phenotype of DGAT2 knockout mice compared to DGAT1 knockouts (nearly absent TG vs. modest reduction) demonstrates that DGAT2 is the predominant enzyme responsible for bulk triglyceride synthesis . When overexpressed in McArdle rat hepatoma cells, DGAT2 caused a much larger increase in intracellular TG levels than DGAT1, further highlighting its dominant role in TG formation .
Research indicates that DGAT1 and DGAT2 utilize different substrate pools for triglyceride synthesis:
DGAT1: Preferentially utilizes phosphatidylcholine (PC)-derived diacylglycerol (DAG) through a channeling mechanism, suggesting a more specialized role in certain lipid metabolism pathways .
DGAT2: Utilizes a larger, more general pool of PC-derived DAG that equilibrates with PC. This enables DGAT2 to incorporate a wider variety of fatty acids into triglycerides .
These differences in substrate utilization partly explain why DGAT2 plays a more significant role in bulk triglyceride synthesis compared to DGAT1. The broader substrate pool accessibility of DGAT2 may be crucial for its ability to efficiently incorporate diverse fatty acids into storage lipids .
For recombinant expression of human DGAT2, several expression systems have been successfully employed, each with specific advantages:
Mammalian expression systems (e.g., HEK293T cells): These provide the most native-like post-translational modifications and membrane environment. Studies have successfully used HEK293T cells for investigating DGAT2 protein-protein interactions and subcellular localization .
Yeast expression systems: Despite limitations for studying typical nuclear-targeted proteins, the split ubiquitin yeast two-hybrid technique has been adapted for membrane-bound enzymes like DGAT2. This system has proven valuable for studying protein-protein interactions between DGAT2 and other membrane-associated proteins involved in lipid metabolism .
Expression validation methodology: When expressing recombinant DGAT2, researchers should verify both expression level and functionality. This typically involves:
Western blotting for protein expression using epitope tags (e.g., FLAG, Myc)
Enzymatic activity assays measuring DAG to TAG conversion
Lipid droplet formation analysis via microscopy with lipid-specific dyes
Several complementary techniques have proven effective for investigating DGAT2 interactions:
Split ubiquitin yeast two-hybrid analysis: This adapted technique is particularly valuable for membrane-bound enzymes like DGAT2. It has successfully demonstrated interactions between DGAT2 and other lipid metabolism enzymes, including LPCAT2 (involved in acyl editing) and PDCT (involved in PC-derived DAG production) .
Co-immunoprecipitation (Co-IP): Studies have utilized epitope-tagged versions of DGAT2 (e.g., FLAG-tagged DGAT2 and Myc-tagged DGAT2) co-expressed in mammalian cells. This approach successfully demonstrated that DGAT2 forms multimeric complexes through interactions between individual subunits .
Deletion mutant analysis: By creating deletion mutants and performing Co-IP experiments, researchers identified that DGAT2 has multiple domains in both N and C termini that mediate subunit interaction .
Analysis of cancer databases has revealed significant insights into DGAT2 mutations in cancer:
Mutation profile: The Catalogue of Somatic Mutations in Cancer (COSMIC) database has identified 398 DGAT2 mutations across 21 different cancer types. The highest frequency of missense mutations occurs in skin tissue samples (f = 21), followed by lungs (f = 16), large intestines (f = 16), and endometrium (f = 15) .
Cancer types: Carcinomas show the highest prevalence of DGAT2 mutations, followed by malignant melanomas. The age distribution reveals that carcinomas and malignant melanomas linked to DGAT2 mutations typically occur in the 50-70 age group .
Mutation significance: While DGAT2 mutations are not identified as cancer drivers, several mutations within the catalytic site show high pathogenicity scores. The D222V mutation represents a notable hotspot, neighboring the Y223H mutation associated with Axonal Charcot-Marie-Tooth disease .
Age correlation: Higher pathogenicity mutations correlate with specimens from patients older than 40 years, with carcinomas and melanomas from older patients showing statistically enriched levels of pathogenic mutations .
| Cancer Tissue | Mutation Frequency | Notable Characteristics |
|---|---|---|
| Skin | 21 | Highest frequency of missense mutations |
| Lung | 16 | High pathogenic score cluster |
| Large Intestine | 16 | High pathogenic score cluster |
| Endometrium | 15 | - |
| Esophagus | Not specified | High pathogenic score cluster |
Recent research has uncovered a crucial role for DGAT2 in flavivirus replication, particularly for Zika virus (ZIKV):
Proviral function: DGAT2 depletion significantly inhibits ZIKV replication in multiple cell lines, and this inhibition can be reversed through trans-complementation with DGAT2. This indicates DGAT2 serves a proviral role in ZIKV infection .
Viral complex recruitment: DGAT2 is recruited into the viral replication complex through direct interactions with non-structural (NS) proteins of the virus .
Protease targeting: Both human and murine DGAT2 can be cleaved by the viral protease NS2B3 at the specific 122R-R-S124 site. This represents a novel mechanism by which DGAT2 is hijacked by the virus .
Functional consequences: The cleaved DGAT2 product becomes more stable and promotes lipid droplet formation independently of its enzymatic activity. This enhanced lipid droplet formation likely provides structural platforms and energy reservoirs that support viral replication .
This mechanism represents a significant insight into host-virus interactions and identifies DGAT2 as a potential therapeutic target for antiviral strategies against flaviviruses.
Understanding and manipulating DGAT2 subcellular localization provides valuable insights into its function:
The discovery that DGAT2 forms multimeric complexes has significant implications for therapeutic development:
Complex formation mechanism: DGAT2 subunits interact through multiple domains in both N and C termini. This multimerization likely affects enzyme activity, substrate accessibility, and interactions with other proteins in lipid metabolic networks .
Drug development considerations:
Targeting protein-protein interaction surfaces between DGAT2 subunits could provide novel mechanisms to modulate activity
Compounds that alter the quaternary structure might have different effects than those targeting the catalytic site
Understanding which regions mediate interactions with different partners could allow selective disruption of specific functions while preserving others
Research methodology: Investigators studying DGAT2 as a drug target should:
Employ techniques like FRET or BRET to study complex formation in living cells
Utilize in silico modeling to identify potential binding pockets at subunit interfaces
Develop assays that can distinguish between effects on catalytic activity versus complex formation
A comprehensive understanding of DGAT2 requires integration of genomic and proteomic approaches:
Multi-omics strategy:
Genomic analysis to identify genetic variants and expression patterns
Transcriptomic profiling to understand tissue-specific expression and splicing
Proteomic approaches to characterize post-translational modifications and interaction partners
Lipidomic analysis to link DGAT2 activity to specific lipid profiles
Research applications:
Correlation between specific DGAT2 mutations and altered lipid profiles in patient samples
Identification of tissue-specific interaction partners that might explain differential functions
Characterization of post-translational modifications that regulate DGAT2 activity in different physiological states
Methodological approach:
CRISPR-Cas9 genome editing to introduce specific mutations
Proximity labeling techniques (BioID, APEX) to identify interaction partners in living cells
Mass spectrometry to characterize post-translational modifications
Single-cell analysis to understand heterogeneity in DGAT2 function within tissues