Recombinant Mouse Fatty acid desaturase 2-like protein FADS2P1 (Fads2p1)

What is Recombinant Mouse Fatty acid desaturase 2-like protein FADS2P1 and what is its role in fatty acid metabolism?

Recombinant Mouse Fatty acid desaturase 2-like protein FADS2P1 (Fads2p1) is a full-length (487 amino acid) protein encoded by the Fads2p1 gene in mice. This protein belongs to the fatty acid desaturase family, which catalyzes the introduction of double bonds at specific positions in fatty acid chains. FADS2P1 is also known as Fads2b or Fatty acid desaturase 2B (pseudogene) .

The protein plays a crucial role in the biosynthesis of polyunsaturated fatty acids (PUFAs), particularly in the conversion of essential fatty acids (linoleic acid and α-linolenic acid) to their longer-chain derivatives. This conversion is vital for the production of biologically active metabolites that regulate numerous physiological processes, including inflammation, neural development, and cardiovascular function.

Methodologically, researchers can study FADS2P1 function by measuring its enzymatic activity through the ratios of specific fatty acid products to substrates, such as γ-linoleic acid to linoleic acid (GLA:LA) .

What are the physical and biochemical properties of recombinant FADS2P1 protein?

The recombinant full-length Mouse FADS2P1 protein has the following key properties:

• Length: 487 amino acids (full-length)

• Molecular Structure: Contains an N-terminal His tag when expressed recombinantly

• Amino Acid Sequence: Complete sequence available (MKLEEKLEHNESLVGKSRPCLHD...WMNAYYE) as documented in the product information

• Expression System: Can be successfully expressed in E. coli for recombinant production

• Physical Form: Typically supplied as a lyophilized powder

• Storage Buffer Compatibility: Stable in Tris/PBS-based buffer with 6% Trehalose at pH 8.0

• Purity: Greater than 90% as determined by SDS-PAGE analysis

For experimental applications, researchers should reconstitute the protein in deionized sterile water to a concentration of 0.1-1.0 mg/mL and consider adding glycerol (5-50% final concentration) for long-term storage at -20°C/-80°C to maintain protein stability. Repeated freeze-thaw cycles should be avoided to preserve protein activity .

What are the optimal conditions for handling and storing recombinant FADS2P1 protein?

For optimal handling and storage of recombinant FADS2P1 protein, researchers should follow these evidence-based protocols:

Reconstitution Protocol:

• Briefly centrifuge the vial prior to opening to ensure all content is at the bottom

• Reconstitute in deionized sterile water to achieve a concentration of 0.1-1.0 mg/mL

• Add glycerol to a final concentration of 5-50% (with 50% being the standard recommendation) for cryoprotection

• Aliquot the reconstituted protein into smaller volumes to avoid repeated freeze-thaw cycles

Storage Conditions:

• Long-term storage: -20°C to -80°C in aliquoted form

• Working aliquots: Can be stored at 4°C for up to one week

• Storage buffer: Tris/PBS-based buffer containing 6% Trehalose, pH 8.0 provides optimal stability

Critical Precautions:

• Avoid repeated freeze-thaw cycles as they significantly compromise protein integrity

• For multiple uses, prepare appropriate working aliquots immediately after reconstitution

• Centrifuge protein solutions briefly prior to use to remove any potential aggregates

These handling protocols ensure maximum retention of enzymatic activity and structural integrity for experimental applications.

How can I assess FADS2P1 enzymatic activity in biological samples?

Assessment of FADS2P1 enzymatic activity in biological samples requires indirect measurement through fatty acid ratios, as direct in vitro assays are challenging. The following methodological approach is recommended:

Fatty Acid Ratio Analysis:

• Extract total lipids from biological samples (plasma, tissue homogenates) using established methods

• Measure fatty acid concentrations using gas chromatography as implemented in studies of FADS enzymatic activity

• Calculate specific fatty acid ratios that reflect desaturase activity:

  • γ-linoleic acid to linoleic acid (GLA:LA) ratio

  • Arachidonic acid to linoleic acid (AA:LA) ratio

  • Arachidonic acid to dihomo-γ-linoleic acid (AA:DGLA) ratio

  • Eicosapentaneoic acid to α-linolenic acid (EPA:ALA) ratio

Technical Procedure:
For precise analysis, use ultra-performance liquid chromatography quadrupole-time-of-flight mass spectrometry (UPLC-QTOFMS):

• Prepare samples using appropriate extraction methods

• Run samples on an ACQUITY-UPLC system equipped with a binary solvent delivery system

• Analyze using tandem quadrupole-time-of-flight (Q-TOF) mass spectrometry

• Include reference standards at appropriate concentrations after every ten samples for quality control

• Process raw data with TargetLynx applications or similar software

• Calculate absolute concentrations using standard curves

These ratios provide an indirect but reliable assessment of FADS2P1 activity, reflecting the enzyme's ability to introduce double bonds into specific fatty acid substrates.

How do polymorphisms in the FADS gene cluster affect FADS2P1 function?

Polymorphisms in the FADS gene cluster significantly impact FADS2P1 function through complex mechanisms affecting gene expression and enzyme activity. Research has revealed:

SNP-Specific Effects on Desaturase Activity:

• Multiple single nucleotide polymorphisms (SNPs) in the FADS gene cluster are associated with altered desaturase activities across different ethnic populations

• In a study of Canadian adults (Caucasian and Asian), 19 SNPs were examined, with 9 SNPs in Caucasians and 8 SNPs in Asians showing significant associations with desaturase activities

• The most significant association was between FADS1 rs174547 SNP and the AA:LA ratio in both Caucasians (p=4.0×10⁻⁸) and Asians (p=5.0×10⁻⁵)

• Carriers of the C allele at rs174547 demonstrated lower desaturase activity than carriers of the T allele, regardless of ethnic background

Molecular Mechanisms:

• Expression quantitative trait locus (eQTL) analysis reveals that the minor allele of rs174570 is associated with decreased FADS1 and FADS2 expression levels (P < 0.05)

• Methylation quantitative trait locus (mQTL) analysis shows that rs174570 affects DNA methylation levels at multiple CpG sites in FADS1 and FADS2

• Methylation levels at specific CpG sites in FADS1 negatively correlate with FADS1 and FADS2 expression, while some CpG sites in FADS2 show positive correlation

These genetic variations explain individual differences in PUFA metabolism and could influence experimental outcomes when studying FADS2P1 in mouse models, particularly when comparing results across different genetic backgrounds.

What methods are recommended for genotyping FADS2 polymorphisms in experimental models?

For accurate genotyping of FADS2 polymorphisms in experimental models, researchers should consider these validated methodological approaches:

Recommended Genotyping Methods:

• Real-Time PCR-Based SNP Genotyping:

  • Utilized successfully for genotyping FADS1 and FADS2 SNPs in human studies

  • Allows for high-throughput screening of samples

  • Provides rapid results with high accuracy

• MALDI-TOF Mass Spectrometry:

  • Successfully employed for genotyping FADS1 and FADS2 in diverse populations

  • Enables multiplex analysis of multiple SNPs simultaneously

  • Offers excellent precision for SNP detection

• Genetic Analyzer DNA Sequencing:

  • Used for targeted genotyping of specific SNPs like rs174570

  • Provides sequence confirmation of genotypes

  • Applied successfully in adipose tissue samples

Procedural Considerations:

• For mouse models, extract genomic DNA from tissue samples (tail biopsies, blood) using standard DNA extraction kits

• Design primers specific to mouse FADS genes, accounting for species-specific sequence variations

• Include appropriate positive and negative controls in each genotyping run

• Validate genotyping results with Sanger sequencing for a subset of samples

• For studies involving epigenetic regulation, combine genotyping with methylation analysis using bisulfite conversion methods

These approaches enable accurate identification of genetic variants in the FADS gene cluster, which is essential for interpreting variations in FADS2P1 function across experimental subjects.

How does FADS2P1 expression and activity differ across tissues in mouse models?

FADS2P1 expression and activity demonstrate significant tissue-specific patterns in mouse models, which has important implications for experimental design. Although the provided search results don't directly address tissue-specific expression of FADS2P1, related research on FADS genes suggests:

Tissue Expression Patterns:

• FADS enzymes show highest expression in metabolically active tissues, particularly the liver as the primary site of fatty acid metabolism

• Significant expression is also observed in adipose tissue, as evidenced by studies examining FADS1 and FADS2 expression in visceral adipose tissue

• Brain tissue expresses FADS enzymes to support local synthesis of long-chain PUFAs crucial for neuronal function

• Expression levels vary with developmental stage, with certain tissues showing higher expression during specific growth phases

Methodological Approaches for Tissue-Specific Analysis:

• Tissue mRNA Expression Analysis:

  • Extract RNA from different mouse tissues using appropriate kits (e.g., RNeasy Plus Universal Kit)

  • Synthesize cDNA using reverse transcription kits (e.g., PrimeScript RT reagent kit)

  • Perform quantitative PCR to measure relative expression of FADS2P1 across tissues

  • Normalize results to appropriate housekeeping genes for each tissue type

• Protein Expression Analysis:

  • Prepare tissue homogenates using appropriate buffers that preserve protein activity

  • Perform Western blot analysis using antibodies specific to FADS2P1

  • Quantify protein levels using densitometry and normalize to loading controls

• Tissue-Specific Activity Assessment:

  • Measure tissue-specific fatty acid profiles using gas chromatography

  • Calculate desaturase activity indices (product-to-precursor ratios) for each tissue

  • Compare enzyme activity across tissues based on these ratios

When designing experiments to study FADS2P1, researchers should consider these tissue-specific differences and select appropriate tissue sources based on their specific research questions.

What are the experimental challenges in differentiating the functions of FADS2P1 from other FADS family members?

Differentiating the specific functions of FADS2P1 from other FADS family members presents several experimental challenges that researchers must address through careful methodological approaches:

Key Challenges:

• Sequence and Functional Homology:

  • High sequence similarity between FADS family members (FADS1, FADS2, FADS3)

  • Overlapping substrate specificity, particularly between FADS1 and FADS2

  • Similar regulation patterns in response to dietary and hormonal factors

• Lack of Highly Specific Inhibitors:

  • Limited availability of inhibitors that selectively target individual FADS enzymes

  • Cross-reactivity of available inhibitors across family members

• Complex Genetic Regulation:

  • The FADS gene cluster contains multiple genes that are co-regulated

  • SNPs can affect multiple FADS genes simultaneously

  • Epigenetic regulation through DNA methylation affects the entire cluster

Methodological Solutions:

• Gene-Specific Knockdown/Knockout Approaches:

  • Use siRNA or CRISPR-Cas9 technology for selective targeting of FADS2P1

  • Generate conditional knockout models to avoid developmental compensation

  • Validate knockdown/knockout efficiency at both mRNA and protein levels

• Recombinant Protein Expression Systems:

  • Express recombinant FADS2P1 in heterologous systems (e.g., E. coli)

  • Perform in vitro enzymatic assays with purified recombinant proteins

  • Compare substrate specificity and kinetic parameters with other FADS family members

• Advanced Analytical Techniques:

  • Employ lipidomic approaches to comprehensively profile fatty acid changes

  • Use stable isotope labeling to track substrate-specific metabolism

  • Analyze specific fatty acid ratios that reflect the activity of different FADS enzymes

• Genetic Correlation Studies:

  • Analyze the effects of specific SNPs on different FADS enzymes

  • Use mediation analysis to explore relationships between genotype, gene expression, and enzyme activity

  • Construct structural equation models to distinguish direct and indirect effects of genetic variants

By implementing these methodological approaches, researchers can more effectively differentiate the specific functions of FADS2P1 from other FADS family members, enabling more precise understanding of its unique biological roles.

How do dietary fatty acids influence FADS2P1 expression and activity in mouse models?

While the search results don't directly address dietary influences on FADS2P1, extensive research on FADS genes suggests significant dietary regulation of FADS2P1 expression and activity in mouse models:

Diet-Gene Interactions:

• Dietary PUFA intake modulates FADS gene expression through feedback mechanisms

• High omega-6 PUFA diets typically downregulate FADS gene expression to prevent excessive production of pro-inflammatory mediators

• Dietary omega-3 PUFAs can alter the balance of fatty acid metabolism through competitive inhibition of the FADS enzymatic pathway

Methodological Approaches to Study Dietary Effects:

• Dietary Intervention Studies:

  • Design controlled feeding studies with defined PUFA compositions

  • Compare diets with varying omega-3:omega-6 ratios to assess differential effects

  • Analyze both acute and chronic dietary interventions to distinguish adaptive responses

  • Measure changes in FADS2P1 mRNA expression, protein levels, and enzyme activity

• Expression Analysis Following Dietary Manipulation:

  • Extract RNA from liver or adipose tissue after dietary intervention

  • Perform quantitative PCR to assess FADS2P1 mRNA levels

  • Normalize to appropriate housekeeping genes

  • Consider the use of RNA-seq for genome-wide expression analysis

• Fatty Acid Profile Analysis:

  • Use gas chromatography or UPLC-QTOFMS to analyze fatty acid profiles

  • Calculate desaturase activity indices based on product-to-precursor ratios

  • Compare these ratios across different dietary conditions

• Integrated Multi-Omics Approach:

  • Combine transcriptomics, proteomics, and lipidomics data

  • Correlate changes in gene expression with alterations in lipid profiles

  • Construct pathway models to explain diet-induced alterations in FADS2P1 function

Understanding these diet-gene interactions is essential for interpreting experimental results and designing nutritional interventions that target FADS2P1-mediated fatty acid metabolism.

What is the relationship between FADS2P1 genetic variants and metabolic phenotypes in experimental models?

The relationship between FADS2P1 genetic variants and metabolic phenotypes represents an area of significant research interest, with important implications for understanding metabolic disorders:

Genetic Variant-Phenotype Associations:

• Weight Regulation:

  • FADS gene polymorphisms have been associated with weight gain in human studies

  • The SNP rs174575 in FADS2 shows a significant positive direct effect on weight gain during pregnancy (coefficient: 0.106; p = 0.016)

  • This suggests potential roles for FADS2P1 variants in energy metabolism and adiposity

• PUFA Metabolism:

  • SNP rs174561 (FADS1) and SNP rs174575 (FADS2) show direct adverse effects on plasma concentrations of omega-3 fatty acids (EPA and alpha-linoleic acid)

  • SNP rs174575 has positive direct effects on plasma levels of arachidonic acid (ARA) and the ARA/LA ratio, affecting omega-6 metabolism

  • SNP rs3834458 (FADS2) demonstrates an adverse effect on plasma EPA concentrations

• Protective Genetic Variants:

  • Heterozygous and homozygous carriers of the minor allele of SNP rs3834458 (FADS2) show higher concentrations of omega-3 substrates, potentially conferring health benefits

Experimental Approaches to Study Variant-Phenotype Relationships:

• Genotype-Specific Mouse Models:

  • Generate mouse models with specific FADS2P1 variants using CRISPR-Cas9 technology

  • Compare metabolic parameters (body weight, adiposity, insulin sensitivity) across genotypes

  • Challenge these models with different diets to assess gene-diet interactions

• Fatty Acid Profiling:

  • Measure comprehensive fatty acid profiles in plasma and tissues using gas chromatography

  • Compare fatty acid ratios (product-to-precursor) to assess desaturase activity

  • Correlate fatty acid profiles with metabolic parameters

• Advanced Statistical Modeling:

  • Apply Structural Equation Modeling to assess direct and indirect effects of genetic variants

  • Perform mediation analysis to understand how genetic effects are mediated through changes in fatty acid metabolism

  • Control for confounding factors such as age, sex, and body mass index

These findings highlight the importance of considering genetic variation in FADS2P1 when designing and interpreting experiments, as genetic background can significantly influence metabolic outcomes related to fatty acid metabolism.

How does epigenetic regulation influence FADS2P1 expression in different experimental contexts?

Epigenetic regulation represents a critical dimension in understanding FADS2P1 expression across different experimental contexts. Recent research has revealed complex interactions between genetic variation, DNA methylation, and gene expression in the FADS gene cluster:

DNA Methylation Patterns and Their Impact:

• CpG Site-Specific Regulation:

  • Methylation levels at specific CpG sites in the FADS gene cluster correlate with gene expression

  • Four CpG sites in FADS1, one in the intragenic region, and three in FADS2 show strong associations with the SNP rs174570

  • Methylation at three CpG sites in FADS1 negatively correlates with FADS1 and FADS2 expression

  • Conversely, methylation at two CpG sites in FADS2 positively correlates with expression of both genes

• Genotype-Dependent Methylation (mQTL):

  • Genetic variants influence DNA methylation patterns in the FADS gene cluster

  • This creates a complex regulatory network where genetic variation affects methylation, which in turn modulates gene expression

Methodological Approaches for Epigenetic Analysis:

• Bisulfite Conversion and Analysis:

  • Perform bisulfite conversion of genomic DNA to distinguish methylated from unmethylated cytosines

  • Design region-specific primers using tools like EpiDesigner

  • Process samples using MassARRAY system for quantitative methylation analysis

  • Calculate relative methylation levels using EpiTYPER software

• Combined Genetic and Epigenetic Analysis:

  • Genotype samples for key SNPs in the FADS gene cluster

  • Analyze DNA methylation at regulatory regions

  • Measure gene expression levels

  • Perform integrated analysis to identify relationships between genotype, methylation, and expression

• Mediation Analysis:

  • Use statistical approaches like the PROCESS procedure to explore relationships between predictor and outcome variables

  • Apply bootstrap analyses with multiple resamples to test the significance of predictor-outcome associations after adding methylation as a covariate

  • Adjust analyses for relevant factors such as age, sex, and BMI

These approaches reveal how epigenetic mechanisms add another layer of complexity to FADS2P1 regulation, potentially explaining tissue-specific and context-dependent variations in enzyme activity that cannot be attributed to genetic factors alone.

What are the most promising experimental models for studying FADS2P1 function in metabolic disease?

Several experimental models offer valuable approaches for investigating FADS2P1 function in metabolic disease, each with unique advantages for addressing specific research questions:

In Vitro Models:

• Recombinant Protein Systems:

  • Expression of recombinant FADS2P1 in E. coli provides a controlled system for enzymatic studies

  • Allows direct assessment of how genetic variants affect protein function

  • Enables high-throughput screening of potential modulators

• Cell Culture Models:

  • Hepatocyte cell lines (primary or immortalized) express FADS genes at physiologically relevant levels

  • Adipocyte models allow investigation of FADS2P1 in fat metabolism

  • Gene editing techniques can introduce specific FADS2P1 variants for functional studies

In Vivo Models:

• Genetically Modified Mouse Models:

  • Knockout or knockin models targeting specific FADS2P1 variants

  • Conditional expression systems to study tissue-specific effects

  • Humanized mouse models expressing human FADS variants for translational studies

• Diet-Induced Metabolic Disease Models:

  • High-fat diet models to study FADS2P1 in obesity and insulin resistance

  • Models with varying dietary PUFA compositions to examine gene-diet interactions

  • Combination of genetic modification with dietary challenges

Methodological Considerations:

• Comprehensive Phenotyping:

  • Measure metabolic parameters (glucose tolerance, insulin sensitivity)

  • Analyze tissue-specific lipid profiles using gas chromatography or UPLC-QTOFMS

  • Assess inflammatory markers that may be influenced by FADS2P1-derived fatty acids

• Multi-Omics Integration:

  • Combine transcriptomics, proteomics, and lipidomics data

  • Apply pathway analysis to understand network effects

  • Use systems biology approaches to model complex interactions

• Translational Approaches:

  • Compare findings from mouse models with human genetic association studies

  • Validate mouse findings using human samples where possible

  • Consider population-specific genetic variations when designing translational studies

The pregnancy cohort model used in recent research demonstrates the value of studying FADS2P1 in specific physiological contexts. This model revealed significant associations between FADS gene polymorphisms and gestational weight gain, providing insights into how these genetic variants influence metabolic adaptations during pregnancy . Similar targeted approaches focusing on specific physiological or pathological states could provide valuable insights into FADS2P1 function in metabolic disease.

What are the current limitations in FADS2P1 research and how might they be addressed?

Current FADS2P1 research faces several methodological and conceptual limitations that researchers should consider when designing experiments:

Current Limitations:

• Functional Redundancy:

  • Overlapping functions between FADS family members complicate interpretation of phenotypes

  • Compensation mechanisms may mask effects in knockout models

  • Difficulty in attributing specific fatty acid changes to individual FADS enzymes

• Species Differences:

  • Variations in FADS gene regulation between mice and humans limit translational relevance

  • Different baseline PUFA metabolism patterns across species

  • Mouse FADS2P1 may have evolved distinct functions from human FADS2

• Complex Regulation:

  • Intricate interplay between genetic variants, epigenetic regulation, and environmental factors

  • Difficulty isolating the effects of individual regulatory elements

  • Context-dependent expression and activity patterns

• Methodological Challenges:

  • Limited availability of specific antibodies for FADS2P1

  • Challenges in measuring enzyme activity directly rather than through product-to-precursor ratios

  • Variability in experimental conditions affecting reproducibility

Potential Solutions:

• Advanced Genetic Models:

  • Develop tissue-specific and inducible knockout systems to minimize developmental compensation

  • Generate allelic series with multiple variants to study dose-dependent effects

  • Create humanized mouse models expressing human FADS genes for better translational relevance

• Improved Analytical Techniques:

  • Develop enzyme assays that directly measure FADS2P1 activity

  • Apply advanced mass spectrometry techniques for more comprehensive lipid profiling

  • Employ stable isotope labeling to track specific metabolic pathways

• Integrative Approaches:

  • Combine genetic, epigenetic, and expression data in unified models

  • Apply systems biology approaches to understand network-level effects

  • Use statistical methods like mediation analysis and structural equation modeling to disentangle complex relationships

• Standardized Protocols:

  • Establish consensus guidelines for experimental conditions

  • Develop reference materials for calibration across laboratories

  • Create repositories for sharing raw data and analytical methods

By addressing these limitations through methodological innovations and integrative approaches, researchers can advance our understanding of FADS2P1 biology and its implications for metabolic health.

How might targeting FADS2P1 offer therapeutic potential for metabolic disorders?

Based on current knowledge of FADS2P1 function and its genetic variations, several therapeutic strategies could potentially target this enzyme for metabolic disorders:

Therapeutic Potential:

• Personalized Nutritional Interventions:

  • Genotype-based dietary recommendations to optimize PUFA intake

  • Tailored omega-3:omega-6 ratios based on FADS2P1 genetic variants

  • Strategic supplementation to compensate for reduced enzymatic activity in certain genotypes

• Pharmacological Modulation:

  • Development of selective FADS2P1 inhibitors to reduce production of pro-inflammatory omega-6 derivatives

  • Allosteric modulators to enhance enzyme activity in carriers of low-activity variants

  • Compounds that target specific regulatory elements affecting FADS2P1 expression

• Epigenetic Approaches:

  • Interventions targeting DNA methylation patterns in the FADS gene cluster

  • Compounds that modify histone modifications to regulate FADS2P1 expression

  • Dietary factors that influence epigenetic regulation of FADS genes

Research Directions for Therapeutic Development:

• Validation in Preclinical Models:

  • Test targeted interventions in genetically modified mouse models

  • Evaluate efficacy in diet-induced metabolic disease models

  • Assess long-term effects and potential compensatory mechanisms

• Biomarker Development:

  • Identify fatty acid profiles that predict response to FADS2P1-targeted interventions

  • Develop accessible testing methods for FADS genotyping and fatty acid profiling

  • Establish clinically relevant cutoffs for intervention

• Clinical Translation:

  • Design proof-of-concept studies in human subjects with specific FADS genotypes

  • Investigate interactions between FADS2P1 variants and dietary interventions

  • Evaluate effects on clinically relevant metabolic outcomes

• Pregnancy-Specific Applications:

  • Develop interventions targeting FADS2P1 function during pregnancy

  • Address the relationship between FADS2 polymorphisms and gestational weight gain

  • Consider the impact on fetal development and long-term metabolic health

The association between FADS2 variants and metabolic outcomes, particularly the relationship between SNP rs174575 and weight gain during pregnancy , suggests that FADS2P1-targeted approaches could have applications in preventing excessive weight gain and associated metabolic complications. Additionally, the observed effects of FADS genes on PUFA metabolism indicate potential for modulating inflammatory pathways implicated in metabolic disorders.