Recombinant Rat Dimethylaniline monooxygenase [N-oxide-forming] 4 (Fmo4)

What is the genomic organization of rat FMO4 and how does it compare to human FMO4?

Rat FMO4 shares significant homology with human FMO4, though with distinct species-specific characteristics. Human FMO4 is encoded by a gene located on chromosome 1q23-q25 and belongs to a cluster of flavin-containing monooxygenase genes . The human FMO4 gene has several external IDs including HGNC: 3772, NCBI Gene: 2329, and Ensembl: ENSG00000076258 .

For rat FMO4 studies, it's important to recognize the evolutionary conservation while acknowledging species-specific variations. When designing primers or targeting strategies for recombinant expression, researchers should account for these differences by:

• Performing comparative sequence alignment between species

• Identifying conserved functional domains

• Considering codon optimization for expression systems

This comparative approach allows for more accurate extrapolation of findings between rat models and human applications in xenobiotic metabolism research.

What are the optimal expression systems for producing recombinant rat FMO4?

When expressing recombinant rat FMO4, selection of an appropriate expression system is critical for obtaining functionally active enzyme. Based on experimental evidence from related FMO protein studies, the following systems offer distinct advantages:

Bacterial Expression Systems:

• E. coli BL21(DE3): Provides high yield but may require refolding due to inclusion body formation

• E. coli Rosetta: Better accommodates rare codons present in rat FMO4 sequence

Eukaryotic Expression Systems:

• Insect cells (Sf9, High Five): Superior for maintaining post-translational modifications

• Mammalian cells (HEK293, CHO): Optimal for preserving native folding and activity

When designing expression protocols, consider incorporating the following elements:

• N-terminal His-tag for purification while preserving C-terminal functional domains

• NADPH-regenerating system during purification to maintain flavin cofactor association

• Expression at lower temperatures (16-18°C) to improve protein folding

These methodological considerations significantly impact enzyme activity and stability in downstream applications.

What detection methods are most effective for validating recombinant rat FMO4 expression?

Multiple complementary approaches should be employed to validate recombinant rat FMO4 expression:

Positive controls should include liver tissue samples from rat, mouse, rabbit, or pig, as FMO4 has demonstrated cross-reactivity across these species . For Western blot applications, HuH-7 cells can serve as a positive control . To enhance specificity, researchers should:

• Include negative controls lacking primary antibody

• Verify band specificity using recombinant protein standards

• Consider dual detection with antibodies targeting different epitopes

These validation steps ensure reliable identification of the recombinant protein before proceeding to functional characterization.

How should researchers design experiments to evaluate rat FMO4 enzymatic activity?

Designing robust experiments for rat FMO4 enzymatic activity requires careful consideration of reaction conditions and substrate selection. An effective experimental design should include:

Reaction Components:

• Purified recombinant FMO4 (5-20 μg/mL)

• NADPH-regenerating system (glucose-6-phosphate, G6P dehydrogenase)

• FAD cofactor (1-5 μM)

• Buffer optimization (typically pH 7.4-8.5)

• Known FMO4 substrates as positive controls

Critical Experimental Variables:

• Temperature (optimal range: 30-37°C)

• Incubation time (establish linear range)

• Substrate concentration series for kinetic determinations

Detection Methods:

• HPLC-MS/MS for metabolite identification

• Spectrophotometric assays monitoring NADPH consumption

• Fluorescence-based assays for specific substrates

When structuring your experimental design, follow the principles of randomization and include appropriate controls to account for non-enzymatic reactions . This systematic approach enables accurate assessment of kinetic parameters and substrate specificity.

What controls are essential in comparative studies between wild-type and variant forms of rat FMO4?

When comparing wild-type rat FMO4 to variant forms or mutants, implementing proper controls is critical for valid interpretation of results:

Essential Controls:

• Enzyme Activity Controls:

  • Heat-inactivated enzyme preparations

  • Known FMO inhibitors (e.g., methimazole) to confirm specificity

  • Parallel reactions with related FMO isoforms to assess selectivity

• Expression Level Controls:

  • Quantitative Western blot analysis to normalize for protein expression

  • mRNA quantification to account for transcriptional differences

  • Co-expressed reporter proteins to monitor transfection/expression efficiency

• Stability Controls:

  • Time-course studies to assess differential protein degradation

  • Analysis of cofactor binding affinity

  • Thermal stability assessments

• System-wide Controls:

  • Empty vector transfections

  • Unrelated recombinant proteins expressed under identical conditions

  • Species-matched positive controls (e.g., liver microsomes)

The experimental design should follow true experimental research principles with randomization and control groups to establish causality . This approach helps distinguish variant-specific effects from experimental artifacts.

How can researchers accurately quantify rat FMO4 expression levels across different tissue samples?

Accurate quantification of rat FMO4 across tissue samples requires a multi-modal approach:

RNA-based Quantification:

• qRT-PCR with validated primers spanning exon-exon junctions

• Digital droplet PCR for absolute quantification

• RNA-Seq with appropriate normalization for comparative analysis

Protein-based Quantification:

• Western blot with validated antibodies (recommended dilution: 1:5000-1:50000)

• ELISA with recombinant protein standards for calibration

• Mass spectrometry-based proteomics with labeled internal standards

Tissue Processing Considerations:

• Standardize sample collection and preservation methods

• Optimize extraction protocols for microsomes (primary FMO4 localization)

• Include mixed-tissue calibrators to control for extraction efficiency

When analyzing tissues with potentially low expression, consider enrichment steps such as subcellular fractionation focused on the endoplasmic reticulum where FMO4 is predominantly localized. For immunohistochemistry applications, the recommended antibody dilution range is 1:200-1:800 for optimal signal-to-noise ratio .

How does rat FMO4 compare to human FMO4 in xenobiotic metabolism studies?

When using rat FMO4 as a model for human xenobiotic metabolism, researchers should consider both similarities and differences:

Similarities:

• Both enzymes catalyze NADPH-dependent oxidation of soft nucleophilic heteroatom centers in xenobiotics

• Conserved FAD cofactor requirement

• Similar subcellular localization (endoplasmic reticulum)

Critical Differences:

• Substrate specificity profiles may vary between species

• Kinetic parameters (Km, Vmax) often differ

• Regulatory mechanisms and tissue distribution patterns show species-specific patterns

To address these differences methodologically:

• Conduct parallel studies with both rat and human recombinant enzymes

• Perform substrate screening across species before detailed kinetic analysis

• Incorporate comparative molecular modeling to identify structural determinants of species differences

• Consider humanized rat models for in vivo studies with human relevance

This comparative approach allows for more accurate extrapolation between rat models and human applications in drug metabolism research.

What role does FMO4 play in hepatocellular carcinoma progression, and how can this be studied in rat models?

Recent research has revealed significant associations between FMO4 and hepatocellular carcinoma (HCC):

Methodological Approaches for Rat Models:

• Genetic Manipulation Strategies:

  • CRISPR/Cas9-mediated knockout of Fmo4 in rat hepatocytes

  • Overexpression systems using adenoviral vectors

  • Conditional knockout models to study temporal effects

• In Vivo Tumor Models:

  • Diethylnitrosamine (DEN)-induced HCC with FMO4 modulation

  • Xenograft models using manipulated rat hepatoma cell lines

  • Orthotopic liver implantation models

• Downstream Analysis:

  • Immunometabolic profiling (as FMO4 status correlates with metabolic signatures)

  • Immune cell infiltration assessment (FMO4 low tumors show distinct immune profiles)

  • Evaluation of bile acid metabolism (highly correlated with FMO4 expression)

When designing these studies, researchers should monitor both FMO4 expression levels and the FMO4-related signature (FRS) developed through LASSO methodology, which has demonstrated prognostic value in HCC cohorts .

How does FMO4 interact with immune system components, and what experimental approaches best capture these interactions?

FMO4 has emerging roles in immune regulation, particularly in the context of hepatocellular carcinoma:

Key Immune Interactions:

• FMO4 low status correlates with increased infiltration of both anti-cancer immune cells (activated CD8+ T cells, CD4+ T cells, M1 macrophages) and pro-cancer immune cells (neutrophils, MDSCs, M2 macrophages, Tregs)

• FMO4 shows negative correlation with immune checkpoint inhibitors including PD1, CTLA4, LAG3, and TIM3

• FMO4 low tumors exhibit elevated T cell inflamed score (TIS) yet show signs of immune exhaustion

Experimental Approaches:

• Co-culture Systems:

  • Hepatocyte-immune cell co-cultures with FMO4 modulation

  • Microfluidic platforms to study dynamic interactions

  • 3D organoid models incorporating immune components

• Cytokine/Chemokine Analysis:

  • Multiplex assays for CCL20/CXCR3 and CXCL1/CXCR2 pathways

  • Targeted analysis of Treg and MDSC recruitment factors

  • Temporal assessment of cytokine production following FMO4 modulation

• Flow Cytometry Panels:

  • Multi-parameter analysis of tumor-infiltrating lymphocytes

  • Assessment of exhaustion markers on CD8+ T cells

  • Evaluation of M1/M2 macrophage polarization

These approaches should be integrated with metabolic analysis, as FMO4 appears to shape immuno-metabolic reconfiguration in the tumor microenvironment .

How can researchers effectively use FMO4 as a prognostic biomarker in experimental cancer models?

Based on clinical findings that FMO4 may serve as a prognostic biomarker in hepatocellular carcinoma , researchers can translate this to experimental models:

Biomarker Development Strategy:

• Expression Analysis:

  • Establish baseline FMO4 expression across normal and diseased tissues

  • Develop quantitative assays with appropriate sensitivity (qPCR, digital PCR, targeted proteomics)

  • Validate antibodies for immunohistochemistry applications (recommended dilutions: 1:200-1:800)

• Prognostic Signature Development:

  • Identify FMO4-associated gene expression patterns (FMO4-related signature, FRS)

  • Apply LASSO or similar machine learning methods to refine signature genes

  • Validate signature in independent sample sets

• Integration with Other Biomarkers:

  • Combine with established prognostic markers

  • Develop multiplexed detection platforms

  • Correlate with functional immune parameters (T cell inflamed score, TIDE score)

• Therapeutic Response Prediction:

  • Evaluate FMO4 status as predictor of response to immunotherapies

  • Assess correlation with immune checkpoint inhibitor efficacy

  • Develop combination biomarker panels for treatment stratification

This methodological framework allows for rigorous validation of FMO4 as a biomarker before clinical translation.

What are the most effective approaches to study the regulatory mechanisms controlling rat FMO4 expression?

Understanding FMO4 regulation requires a comprehensive approach to capture multiple levels of control:

Transcriptional Regulation:

• Promoter analysis using luciferase reporter assays

• ChIP-seq to identify transcription factor binding sites

• CRISPR-based screening of potential regulatory elements

• Analysis of epigenetic modifications (DNA methylation, histone modifications)

Post-transcriptional Regulation:

• miRNA binding site prediction and validation

• RNA-protein interaction studies (RIP-seq)

• mRNA stability assays following actinomycin D treatment

• Alternative splicing analysis using RT-PCR and RNA-seq

Post-translational Regulation:

• Phosphoproteomic analysis to identify modification sites

• Protein stability assessment following inhibition of degradation pathways

• Co-immunoprecipitation to identify regulatory protein partners

• In vitro enzymatic assays with potential modifiers

When studying the bile acid pathway, which shows high correlation with FMO4 expression , researchers should specifically examine bile acid-responsive nuclear receptors (FXR, PXR) as potential regulators of FMO4 transcription.

How can researchers develop specific inhibitors or activators of rat FMO4 for experimental applications?

Development of specific modulators for rat FMO4 requires a systematic drug discovery approach:

Target Validation and Assay Development:

• Establish robust in vitro enzymatic assays with recombinant protein

• Develop cell-based reporter systems for FMO4 activity

• Identify species-specific structural features for selective targeting

• Validate assay performance with known FMO family modulators

Screening Strategies:

• Structure-based virtual screening using homology models

• Fragment-based screening against purified protein

• High-throughput enzymatic assays with diverse compound libraries

• Phenotypic screening in FMO4-expressing cell systems

Lead Optimization:

• Structure-activity relationship studies focusing on selectivity

• ADME property optimization for in vivo applications

• Testing in microsomes to assess metabolic stability

• Counter-screening against other FMO family members

Validation in Biological Systems:

• Verification of target engagement using cellular thermal shift assays

• Assessment of pathway modulation using transcriptomics/proteomics

• Evaluation in relevant disease models (e.g., hepatocellular carcinoma models)

• Correlation with FMO4-related metabolic and immune signatures

This systematic approach facilitates development of selective tools for mechanistic studies and potential therapeutic applications.

What strategies help overcome stability issues when working with recombinant rat FMO4?

FMO family proteins, including FMO4, present stability challenges that require specific methodological approaches:

Protein Expression Optimization:

• Lower induction temperatures (16-18°C) to improve folding

• Co-expression with molecular chaperones (GroEL/ES, DnaK)

• Use of solubility-enhancing fusion partners (MBP, SUMO)

• Codon optimization for expression host

Stabilization During Purification:

• Inclusion of glycerol (15-20%) in all buffers

• Addition of FAD cofactor (1-5 μM) throughout purification

• Use of protease inhibitor cocktails optimized for microsomal proteins

• Maintenance of reducing environment with DTT or β-mercaptoethanol

Storage Conditions:

• Flash-freezing in liquid nitrogen with cryoprotectants

• Assessment of activity retention after freeze-thaw cycles

• Evaluation of lyophilization with suitable excipients

• Stability testing under various temperature conditions

For applications requiring extended stability, consider immobilization strategies or the development of stabilized variants through protein engineering approaches.

How can researchers address the challenge of distinguishing FMO4 activity from other FMO family members in complex biological samples?

Differentiating FMO4 activity from other FMO isoforms requires selective experimental approaches:

Selective Inhibition Strategies:

• Use of isoform-selective inhibitors where available

• Temperature-dependent inactivation profiles (FMO4 shows distinct thermal stability)

• pH-dependent activity profiles for differential inhibition

• Co-factor dependency differences between isoforms

Substrate Selection Approaches:

• Identification of FMO4-selective substrates through screening

• Development of isoform-specific activity probes

• Kinetic analysis with substrates showing differential parameters

• Competitive substrate approaches to determine relative contributions

Genetic Manipulation:

• siRNA/shRNA knockdown of specific FMO isoforms

• CRISPR/Cas9-mediated knockout cell lines

• Heterologous expression of individual isoforms

• Use of tissues from FMO-knockout animal models

Analytical Separation:

• Isoform separation by chromatographic methods

• Immunodepletion using isoform-specific antibodies

• Activity-based protein profiling with selective probes

• Mass spectrometry-based proteomic identification

These complementary approaches enable reliable attribution of metabolic activity to FMO4 in complex systems.

What are the key considerations when translating findings from rat FMO4 studies to human applications?

Translating findings from rat to human systems requires careful consideration of several factors:

Species Differences Assessment:

• Comparative sequence and structural analysis of rat vs. human FMO4

• Side-by-side activity assays with recombinant proteins from both species

• Evaluation of tissue expression patterns across species

• Analysis of regulatory mechanisms and their conservation

Scaling Approaches:

• In vitro-to-in vivo extrapolation using physiologically-based models

• Allometric scaling with appropriate species factors

• Consideration of differences in metabolic rates and body composition

• Integration of species-specific pharmacokinetic parameters

Translational Models:

• Humanized rodent models expressing human FMO4

• Ex vivo studies with human tissue samples

• Chimeric liver models with human hepatocytes

• 3D organoid systems derived from human tissues

Regulatory and Clinical Considerations:

• Biomarker validation in human samples

• Correlation of animal model findings with human disease data

• Development of translational biomarkers for clinical studies

• Evaluation of polymorphic variants in human populations

When considering FMO4 as a prognostic biomarker for conditions like hepatocellular carcinoma , validation in human cohorts is essential before clinical application.