Recombinant Pig Methylsterol monooxygenase 1 (MSMO1)

What is MSMO1 and what is its primary function in porcine systems?

MSMO1 (Methylsterol Monooxygenase 1) is a protein-coding gene that plays a crucial role in cholesterol biosynthesis in porcine systems. It is localized to the endoplasmic reticulum membrane and contains metal binding motifs essential for its catalytic activity. The protein functionally resembles the yeast ERG25 protein and is primarily involved in the demethylation of specific sterol precursors .

In biochemical terms, MSMO1 catalyzes a three-step monooxygenation reaction to remove methyl groups from 4,4-dimethyl and 4α-methylsterols, which is an essential process in the conversion of these sterols into cholesterol. This enzymatic activity positions MSMO1 as a key regulator in the porcine sterol biosynthesis pathway .

How does porcine MSMO1 differ from its human ortholog?

While the fundamental catalytic function of MSMO1 is conserved between porcine and human orthologs, there are notable species-specific differences that researchers should consider:

The species-specific differences necessitate careful consideration when designing experiments involving recombinant pig MSMO1, particularly when comparing results to human systems or when developing targeting strategies for the protein .

What experimental models are most suitable for studying recombinant pig MSMO1?

For studying recombinant pig MSMO1, researchers have successfully employed several experimental models:

• Porcine cell lines: Primary porcine cell cultures and established cell lines provide a native cellular environment for MSMO1 expression studies .

• Transgenic porcine models: Reporter pig strains, such as the SRM1 transgenic reporter, enable visualization of successful genetic manipulations and protein expression patterns .

• Recombinant expression systems: Heterologous expression systems using advanced vectors have been optimized for porcine protein expression, with particular success in mammalian expression systems .

The selection of an appropriate model should be guided by the specific research question, with transgenic porcine models offering the most physiologically relevant context for in vivo studies of MSMO1 function, while recombinant expression systems provide greater experimental control for biochemical characterization .

What are the optimal conditions for expressing recombinant pig MSMO1 in vitro?

The optimal conditions for expressing recombinant pig MSMO1 in vitro require careful consideration of several parameters:

Expression System Selection:

• Mammalian expression systems (particularly HEK293 or CHO cells) generally yield properly folded and functional porcine MSMO1 with appropriate post-translational modifications

• Baculovirus-insect cell systems may offer higher yields while maintaining most essential post-translational modifications

• E. coli systems are not recommended due to the membrane-bound nature of MSMO1 and its requirement for specific post-translational modifications

Vector Design Considerations:

• Inclusion of a weak to moderate strength promoter often yields better results than strong viral promoters, which can lead to protein aggregation

• Incorporation of a cleavable purification tag (preferably C-terminal) is recommended

• Codon optimization for the expression host improves yield

• Consider including chaperone co-expression constructs to enhance proper folding

Optimized Culture Conditions:

• Maintain cultures at lower temperatures (28-32°C) during the expression phase to promote proper folding

• Supplement media with heme precursors and iron sources as MSMO1 has metal binding motifs

• Use gentle induction protocols to prevent overwhelming cellular machinery

• For membrane-associated expression, consider supplementation with specific lipids

Researchers should validate proper expression and folding through activity assays targeting the monooxygenase function before proceeding to larger-scale expressions.

How can CRISPR-Cas9 techniques be used to study MSMO1 function in porcine models?

CRISPR-Cas9 techniques offer powerful approaches for investigating MSMO1 function in porcine models:

sgRNA Design for Porcine MSMO1:

• Target selection should consider species-specific sequences in the porcine MSMO1 gene

• Validation of sgRNA efficiency in porcine cell lines is essential before in vivo application

• Multiple sgRNAs should be tested to identify optimal targeting sequences

Delivery Methods for Porcine Studies:

• For in vivo editing, subretinal administration of Cas9 ribonucleoproteins (eRNPs) has shown efficacy in porcine models

• Electroporation has demonstrated success for cellular models, particularly when co-delivered with enhancing factors such as the microRNA-302/367 cluster

Monitoring Editing Efficiency:

• Transgenic reporter systems, such as the SRM1 porcine reporter model where successful editing activates tdTomato expression, provide visual confirmation of editing

• Molecular validation through sequencing and functional assays remains essential

Practical Implementation Protocol:

• Design and validate multiple sgRNAs targeting porcine MSMO1 in vitro

• Complex validated sgRNAs with Cas9 protein to form eRNPs

• Deliver to target tissues using optimized protocols (e.g., subretinal injection at 15 μM concentration)

• Evaluate editing efficiency through molecular techniques and functional assays

• For phenotypic analysis, monitor sterol metabolism and downstream pathways

This approach enables precise genetic manipulation of MSMO1 to investigate its role in cholesterol biosynthesis and other potential functions in porcine models.

What strategies can overcome challenges in purifying active recombinant pig MSMO1?

Purifying active recombinant pig MSMO1 presents several challenges due to its membrane association and enzymatic complexity. The following strategies have proven effective:

Solubilization and Extraction:

• Use mild detergents like DDM (n-Dodecyl β-D-maltoside) or CHAPS at low concentrations for initial solubilization

• Implement a two-step extraction process: first with a gentle detergent, followed by a more stringent but enzyme-compatible detergent

• Consider detergent screening to identify optimal conditions for maintaining enzymatic activity

Chromatography Approach:

• Begin with affinity chromatography using engineered tags (His6 or Strep tags show good results)

• Follow with size exclusion chromatography to separate monomeric from aggregated forms

• Ion exchange chromatography as a polishing step improves purity while preserving activity

Stabilization Strategies:

• Include glycerol (10-15%) in all buffers to maintain protein stability

• Add appropriate metal ions (e.g., iron) to stabilize metal binding motifs

• Consider reconstitution into nanodiscs or liposomes for long-term stability of the purified protein

Activity Preservation:

• Minimize exposure to oxidizing conditions throughout the purification process

• Include reducing agents like DTT or TCEP at appropriate concentrations

• Validate enzymatic activity at each purification step to ensure the protocol preserves function

Implementation of these strategies has enabled researchers to obtain highly purified, active recombinant pig MSMO1 suitable for structural and functional studies.

How should researchers design experiments to study MSMO1 interactions with other proteins in the cholesterol biosynthesis pathway?

Designing experiments to elucidate MSMO1 interactions requires a multi-faceted approach:

Co-Immunoprecipitation Studies:

• Use epitope-tagged recombinant pig MSMO1 expressed in porcine cells

• Perform reciprocal pull-downs with suspected interaction partners

• Include appropriate controls (e.g., catalytically inactive MSMO1 mutants)

• Validate interactions through Western blotting with specific antibodies

Proximity Labeling Approaches:

• Implement BioID or APEX2 fusion constructs with MSMO1 to identify proximal proteins in living cells

• Express in porcine cell lines to maintain native interactome context

• Analyze labeled proteins using mass spectrometry

• Validate highest-confidence hits with orthogonal methods

Functional Validation:

• Employ CRISPR-based knockdown/knockout of identified interaction partners

• Analyze effects on MSMO1 localization, stability, and enzymatic activity

• Reconstitute with mutant versions to map interaction domains

• Quantify effects on cholesterol biosynthesis pathway intermediates and products

Visualization Strategies:

• Utilize fluorescence resonance energy transfer (FRET) to visualize interactions in live cells

• Consider split-protein complementation assays for binary interaction validation

• Implement super-resolution microscopy to define spatial relationships in the endoplasmic reticulum

These approaches provide complementary data to build a comprehensive understanding of MSMO1's role in protein complexes within the cholesterol biosynthesis pathway.

What controls are essential when analyzing the effects of MSMO1 genetic modifications in porcine models?

When analyzing effects of MSMO1 genetic modifications in porcine models, implementing rigorous controls is crucial:

Genetic Controls:

• Include littermate wild-type controls to minimize genetic background variation

• Use non-targeting CRISPR controls that undergo the same delivery procedure but target non-relevant genomic regions

• For transgenic approaches, include animals expressing catalytically inactive MSMO1 variants

Analytical Controls:

• Measure multiple sterol intermediates, not just end-products, to identify specific blockade points

• Implement stable isotope labeling to track metabolic flux through the pathway

• Include technical controls in all analytical procedures (particularly important for mass spectrometry-based sterol analysis)

Phenotypic Assessment Controls:

• Blind observers to genotype during phenotypic assessments

• Establish baseline measurements before genetic manipulation when using inducible systems

• Include age-matched and sex-matched controls for all analyses

Tissue-Specific Considerations:

• For tissue-specific manipulations (e.g., subretinal administration), analyze both treated and untreated regions within the same animal

• Collect samples from multiple tissue types to assess non-specific effects

• Consider temporal controls if using inducible systems

Proper implementation of these controls enables confident attribution of observed effects to MSMO1 modification rather than experimental variables or non-specific effects.

How can researchers distinguish between direct and indirect effects of MSMO1 manipulation on gene expression?

Distinguishing between direct and indirect effects of MSMO1 manipulation requires sophisticated experimental approaches:

Time-Course Analysis:

• Implement time-resolved sampling after MSMO1 manipulation

• Early transcriptional changes (0-6 hours) more likely represent direct effects

• Later changes (24+ hours) often reflect secondary adaptations and compensatory mechanisms

Combining Approaches:

• Integrate transcriptomic data with chromatin immunoprecipitation (ChIP) studies of transcription factors

• Correlate gene expression changes with metabolite alterations (metabolomics)

• Use systems biology approaches to model causal relationships

Rescue Experiments:

• Supplement with pathway intermediates downstream of MSMO1 to determine which gene expression changes can be reversed

• Express catalytically inactive MSMO1 to separate structural from enzymatic effects

• Implement orthogonal pathway modulation to validate mechanisms

Data Analysis Framework:

• Apply pathway enrichment analysis to identify coordinated gene expression changes

• Use comparative analysis across different genetic backgrounds to identify consistent effects

• Implement machine learning approaches to distinguish primary from secondary effects

This methodical approach helps researchers delineate the complex gene regulatory networks affected by MSMO1 manipulation, separating direct enzymatic consequences from broader cellular adaptations.

How should researchers interpret contradictory results between in vitro and in vivo studies of recombinant pig MSMO1?

When faced with contradictory results between in vitro and in vivo studies of recombinant pig MSMO1, researchers should consider several factors:

Potential Sources of Discrepancies:

Methodological Approach to Resolve Contradictions:

• Validate protein structure and modifications in both systems

• Assess enzymatic activity using identical substrates and analytical methods

• Evaluate protein-protein interactions in both contexts

• Consider temporal aspects of the experiments (acute vs. chronic effects)

Interpretative Framework:

This systematic approach transforms contradictory results into valuable insights about context-dependent MSMO1 function and regulation.

What statistical approaches are most appropriate for analyzing MSMO1-related differential gene expression data?

When analyzing MSMO1-related differential gene expression data, selecting appropriate statistical approaches is critical:

Preprocessing Considerations:

• Implement robust normalization methods appropriate to the sequencing platform used

• Evaluate and correct for technical covariates (batch effects, sequencing depth)

• Consider transformations to address heteroscedasticity in expression data

Differential Expression Analysis:

• For designs with limited replicates (<5 per group), utilize methods with moderated variance estimation (e.g., DESeq2, edgeR)

• For complex designs with multiple factors, implement linear models with appropriate contrast matrices

• Apply correction for multiple testing using Benjamini-Hochberg FDR approach with q-value threshold of 0.05

Pathway and Network Analysis:

• Implement Gene Set Enrichment Analysis (GSEA) rather than simple overrepresentation analysis

• Consider topology-aware methods that incorporate pathway structure information

• Use weighted correlation network analysis (WGCNA) to identify co-expressed gene modules

Validation Approaches:

• Select representative genes spanning the range of fold changes for qRT-PCR validation

• Implement cross-validation approaches when sample sizes permit

• Consider independent datasets or alternative models for external validation

Recommended Analytical Workflow:

• Quality assessment and preprocessing of raw data

• Differential expression analysis with appropriate methods for experimental design

• Pathway enrichment analysis focused on lipid metabolism pathways

• Network analysis to identify co-regulated gene modules

• Validation of key findings with orthogonal methods

This comprehensive statistical approach provides robust identification of genes and pathways affected by MSMO1 manipulation while minimizing false discoveries.

How can researchers effectively combine proteomics and transcriptomics data to understand MSMO1 regulatory networks?

Effectively integrating proteomics and transcriptomics data provides comprehensive insights into MSMO1 regulatory networks:

Data Integration Strategies:

• Implement multi-omics factor analysis (MOFA) to identify factors explaining variation across datasets

• Use canonical correlation analysis (CCA) to find associations between protein and transcript levels

• Apply pathway-level integration to identify concordantly regulated biological processes

Handling Temporal Considerations:

• Account for the delay between transcriptional changes and protein abundance alterations

• Implement time-course designs with staggered sampling for transcriptomics and proteomics

• Use dynamic Bayesian networks to model temporal relationships between transcript and protein changes

Specific Analytical Approaches:

• Direct Correlation Analysis:

  • Calculate Spearman/Pearson correlations between transcript and protein levels for each gene

  • Identify genes with discordant changes suggesting post-transcriptional regulation

• Network-Based Integration:

  • Construct separate co-expression networks for transcriptomic and proteomic data

  • Identify network preservation and divergence across data types

  • Map MSMO1 position in both networks to identify context-specific interactions

• Causal Modeling:

  • Implement causal inference methods to predict directionality of relationships

  • Use perturbation data (e.g., MSMO1 knockdown/overexpression) to validate causal predictions

Visualization and Interpretation:

• Create integrated heatmaps showing transcript and protein changes side-by-side

• Visualize network diagrams highlighting concordant and discordant relationships

• Develop chord diagrams to illustrate relationships between transcript and protein modules

This integrative approach reveals both transcriptional and post-transcriptional regulatory mechanisms affecting MSMO1 function and downstream pathways, providing a comprehensive systems-level understanding.

How can findings from recombinant pig MSMO1 research be translated to human disease contexts?

Translating findings from recombinant pig MSMO1 research to human disease contexts requires careful consideration of species similarities and differences:

Comparative Analysis Framework:

• Perform detailed sequence and structural comparisons between pig and human MSMO1

• Identify conserved functional domains and regulatory motifs

• Map any identified disease-relevant mutations in human MSMO1 to equivalent positions in the porcine protein

Translational Research Strategies:

• Develop humanized porcine models expressing human MSMO1 variants

• Create parallel experimental systems with both porcine and human MSMO1 for direct comparison

• Validate key findings in human cell lines and patient-derived samples when available

Disease-Specific Considerations:

• For metabolic disorders: Compare sterol profiles between porcine models and human patients

• For developmental disorders: Assess conserved developmental pathways affected by MSMO1 dysfunction

• For potential therapeutic applications: Evaluate cross-species conservation of drug binding sites

Collaborative Approach:

• Establish collaborations between veterinary and medical researchers

• Implement consistent experimental protocols across species

• Create shared databases of functional variants and their phenotypic effects

This translational framework maximizes the clinical relevance of findings from recombinant pig MSMO1 research while acknowledging and accounting for species-specific differences.

What considerations are important when designing recombinant pig MSMO1 for structural studies?

Designing recombinant pig MSMO1 for structural studies presents specific challenges that require careful consideration:

Construct Design Strategies:

• Create truncated constructs removing flexible termini while preserving core catalytic domains

• Consider fusion proteins with crystallization chaperones (T4 lysozyme, BRIL) inserted into non-conserved loops

• Design thermostable variants through computational prediction and directed evolution

• Implement systematic cysteine mutagenesis to reduce conformational heterogeneity

Expression System Selection:

• For X-ray crystallography: Insect cell expression often provides optimal balance of yield and proper folding

• For Cryo-EM: Mammalian expression systems may better preserve native conformations

• For NMR studies: Consider specialized isotope labeling schemes requiring adapted expression systems

Purification Considerations:

• Implement mild detergent screening to identify conditions that extract MSMO1 while maintaining structural integrity

• Consider reconstitution into nanodiscs or amphipols for membrane protein structural studies

• Develop monodisperse preparations through rigorous size exclusion chromatography and dynamic light scattering validation

Protein Engineering Approaches:

• Introduce surface mutations to enhance crystallization propensity while preserving core structure

• Consider antibody fragment co-crystallization to stabilize flexible regions

• For difficult regions, implement domain-focused approaches studying individual domains

By implementing these specialized approaches, researchers can overcome the inherent challenges of membrane protein structural biology and obtain valuable structural information about recombinant pig MSMO1.

What emerging technologies could advance our understanding of MSMO1 function in porcine models?

Several emerging technologies show exceptional promise for advancing MSMO1 research in porcine models:

Spatial Transcriptomics and Proteomics:

• Implementation of spatial omics approaches to map MSMO1 expression and activity across tissues with subcellular resolution

• Integration with metabolic imaging to correlate MSMO1 distribution with sterol intermediates

• Development of porcine-specific spatial molecular atlases incorporating MSMO1 regulatory networks

Advanced Genome Editing:

• Base editing approaches for introducing precise point mutations mimicking human MSMO1 variants

• Prime editing for introducing complex modifications without double-strand breaks

• Epigenome editing to study regulatory mechanisms controlling MSMO1 expression

Organoid Technologies:

• Development of porcine liver and adrenal organoids for studying MSMO1 in tissue-specific contexts

• Co-culture systems to investigate intercellular communication influenced by MSMO1 activity

• Patient-derived xenografts in immunocompromised pigs for translational studies

Single-Cell Multi-Omics:

• Single-cell approaches to identify cell-type-specific MSMO1 functions

• Multi-modal single-cell profiling combining transcriptomics, proteomics, and metabolomics

• Trajectory analysis to map MSMO1's role in cell state transitions during development and disease

These technologies will enable unprecedented insights into MSMO1 biology, revealing its tissue-specific functions, regulatory mechanisms, and potential as a therapeutic target.

How might systems biology approaches enhance our understanding of recombinant pig MSMO1 in metabolic pathways?

Systems biology approaches offer powerful frameworks for understanding recombinant pig MSMO1's role in metabolic networks:

Genome-Scale Metabolic Modeling:

• Development of porcine-specific genome-scale metabolic models incorporating MSMO1

• Flux balance analysis to predict metabolic consequences of MSMO1 perturbations

• Integration of transcriptomic data to create context-specific models under different conditions

Network Medicine Approaches:

• Construction of sterol metabolism-focused interactomes centered on MSMO1

• Network perturbation analysis to identify critical nodes influencing MSMO1 function

• Application of network-based drug target identification methods

Multi-Scale Modeling:

• Integration of molecular dynamics simulations of MSMO1 with cellular metabolic models

• Development of tissue-specific models connecting MSMO1 activity to physiological outcomes

• Whole-body physiological modeling to predict systemic effects of MSMO1 manipulation

Implementation Strategy:

• Generate comprehensive multi-omics datasets from porcine models with MSMO1 perturbations

• Develop computational models integrating these datasets

• Validate model predictions with targeted experimental approaches

• Refine models iteratively to improve predictive power

This systems biology framework transforms isolated findings into a comprehensive understanding of MSMO1's position within the broader metabolic network, enabling prediction of intervention effects and identification of potential compensatory mechanisms.

What are the most promising applications of recombinant pig MSMO1 in comparative medicine?

Recombinant pig MSMO1 offers several promising applications in comparative medicine:

Comparative Disease Modeling:

• Development of porcine models expressing human MSMO1 variants associated with metabolic disorders

• Investigation of species-specific differences in sterol metabolism with implications for cardiovascular disease

• Comparative studies of MSMO1 function across species to identify evolutionarily conserved mechanisms

Therapeutic Development Platform:

• Screening for MSMO1 modulators in porcine systems as preclinical models

• Assessment of tissue-specific effects and potential off-target consequences

• Evaluation of delivery methods for MSMO1-targeting therapeutics

One Health Applications:

• Investigation of MSMO1's role in diseases affecting both humans and pigs

• Development of interventions with dual veterinary and medical applications

• Study of environmental factors affecting MSMO1 function across species

Translational Research Framework:

• Implementation of parallel studies in porcine models and human samples

• Development of biomarkers reflecting MSMO1 activity applicable across species

• Creation of comparative databases documenting MSMO1 variants and their phenotypic effects

These applications leverage the unique advantages of porcine models while developing translational insights relevant to human health, advancing both veterinary and medical research in complementary ways.