SERAC1 (serine active site domain-containing protein 1) is a 654-amino acid protein containing a conserved serine-lipase domain with a consensus lipase motif GxSxG. It belongs to the PGAP-like protein domain family (PFAM PF07819) . The protein localizes to the outer mitochondrial membrane and functions at the interface between the endoplasmic reticulum and mitochondria .
Functionally, SERAC1:
Participates in phospholipid remodeling, particularly converting phosphatidylglycerol-34:1 (PG-34:1) to phosphatidylglycerol-36:1 (PG-36:1)
Acts as a component of the mitochondrial serine transporter system by interacting with SFXN1 to transport serine from cytosol to mitochondria
Participates in the one-carbon metabolism cycle essential for nucleotide synthesis
Several experimental models have been documented in the literature for SERAC1 research:
Cellular Models:
Animal Models:
In vitro Systems:
Recombinant protein expression systems for structural and functional studies
Mitochondrial assays to study SERAC1's role in phospholipid remodeling
When selecting an experimental model, researchers should consider the specific aspect of SERAC1 function they wish to investigate. For mitochondrial function studies, both cellular and animal models provide valuable platforms for investigating physiological impacts of SERAC1 dysfunction.
Several methodological approaches can be employed to study SERAC1 protein interactions:
Co-immunoprecipitation (Co-IP): This approach has been utilized to demonstrate SERAC1's interaction with SFXN1, the mitochondrial serine transporter protein .
Proximity Labeling Methods: BioID or APEX2 proximity labeling can identify proteins in close proximity to SERAC1 within the mitochondrial outer membrane environment.
Fluorescence Resonance Energy Transfer (FRET): This technique can confirm direct protein-protein interactions in living cells.
Yeast Two-Hybrid Screening: Although not specifically mentioned in the provided materials, this approach could identify novel interaction partners.
Pull-down Assays with Recombinant Proteins: Using purified recombinant SERAC1 to identify direct binding partners from cellular lysates.
For bovine SERAC1 studies, these methods would need to be optimized using species-specific antibodies or recombinant proteins to ensure accurate detection of interaction partners.
SERAC1 contributes to the one-carbon metabolism cycle by facilitating serine transport into mitochondria through interaction with the SFXN1 transporter . This process is crucial for maintaining proper nucleotide pools within mitochondria.
Metabolite Analysis:
Isotope Tracing:
Use ^13^C-labeled serine to track carbon flux through the one-carbon cycle
Analyze incorporation of labeled carbon into nucleotides and other downstream metabolites
Functional Assays:
Research has demonstrated that loss of SERAC1 impairs the one-carbon cycle and disrupts the nucleotide pool balance, leading to mitochondrial DNA depletion. Importantly, both in vitro and in vivo supplementation of nucleosides/nucleotides can restore mitochondrial DNA content and function in SERAC1-deficient systems .
Phenotypic Variability:
Challenge: SERAC1 mutations can present with a spectrum of phenotypes ranging from severe MEGDEL syndrome to milder complicated hereditary spastic paraplegia (cHSP) .
Solution: Develop standardized phenotyping criteria and use multi-parameter assessment to capture the full range of effects. Implement matched controls and consider age-dependent effects in experimental design.
Genotype-Phenotype Correlation:
Challenge: No clear relationship between specific SERAC1 variants and phenotypes has been established .
Solution: Employ comprehensive mutation analysis coupled with functional assays to classify variants. Use CRISPR-Cas9 to introduce specific mutations in cellular or animal models for direct comparison.
Functional Assessment:
Challenge: Determining the functional impact of missense variants in the serine-lipase domain versus frameshift mutations.
Solution: Develop in vitro enzyme activity assays to measure lipase function. For novel variants, use predictive software in combination with conservation analysis:
| Analysis Tool | Result for Missense Variant | Interpretation |
|---|---|---|
| PolyPhen-2 | Probably Damaging | Likely pathogenic |
| SIFT | Deleterious | Likely pathogenic |
| MutationTaster | Disease Causing | Likely pathogenic |
| Conservation | Highly conserved across species | Functionally important |
Biochemical Markers:
Subcellular Fractionation and Imaging:
Separate mitochondria-associated membranes (MAMs) where SERAC1 functions at the ER-mitochondria interface
Use super-resolution microscopy with fluorescently tagged SERAC1 to visualize its dynamic localization
Lipid Profiling:
Cholesterol Transport Assays:
Use fluorescent cholesterol analogs to track intracellular movement
Measure cholesterol distribution in cellular compartments using filipin staining
Assess effects of SERAC1 mutations on cholesterol-dependent cellular processes
Domain-Specific Mutagenesis:
Create targeted mutations in different functional domains of SERAC1:
Express these mutants in SERAC1-deficient cells to assess rescue of specific functions
Biochemical Reconstitution:
Purify recombinant SERAC1 protein (wild-type and mutant versions)
Reconstitute with artificial membranes to directly measure phospholipid remodeling activity
Test cholesterol transfer between membrane vesicles in vitro
SERAC1 deficiency manifests with tissue-specific effects, particularly affecting the nervous system, hearing, liver, and mitochondria-rich tissues . To investigate these tissue-specific manifestations:
Tissue-Specific Conditional Knockout Models:
Generate tissue-specific Cre-loxP conditional knockout mice to eliminate SERAC1 in specific tissues (brain, liver, cochlea)
Compare phenotypes across different tissue-specific knockouts to isolate primary versus secondary effects
Cell-Type Specific Analyses:
Derive different cell types (neurons, hepatocytes, cochlear hair cells) from patient iPSCs or through directed differentiation of SERAC1-knockout stem cells
Compare mitochondrial function, phospholipid composition, and cellular responses across cell types
Multi-Omics Integration:
Apply transcriptomics, proteomics, and metabolomics to tissues from SERAC1-deficient models
Identify tissue-specific pathways affected by SERAC1 dysfunction
Data integration table example:
| Tissue | Transcriptomic Changes | Proteomic Changes | Metabolomic Changes | Functional Impact |
|---|---|---|---|---|
| Brain | ↓ mitochondrial genes | ↓ respiratory chain complexes | ↑ lactate, ↓ ATP | Energy deficit, neurodegeneration |
| Liver | ↑ stress response genes | ↓ metabolic enzymes | Altered lipid profiles | Hepatic dysfunction |
| Cochlea | ↓ ion transport genes | ↓ membrane proteins | Altered phospholipids | Hearing loss |
Ex Vivo Tissue Explants:
Culture tissue explants from SERAC1-deficient models
Test tissue-specific responses to metabolic stressors
Evaluate tissue-specific rescue with nucleotide supplementation or gene therapy approaches
Based on published protocols, the following methodological approach is recommended for SERAC1 mutation detection:
Extract DNA from whole blood using QIAamp DNA Blood Mini kit or equivalent
Alternatively, use saliva or skin fibroblasts as DNA sources
Design primers spanning all 17 exons and flanking intronic regions
For exon 10, which contains several reported pathogenic variants, use:
PCR conditions:
Use high-fidelity DNA polymerase for accurate amplification
Sanger Sequencing:
Next-Generation Sequencing:
Whole Exome Sequencing (WES) for comprehensive variant detection
Target enrichment of SERAC1 and related genes
Minimum coverage of 30× recommended for reliable variant calling
Use bioinformatics software (e.g., Alamut Visual) to predict pathogenicity
Apply ACMG guidelines for variant classification
Guide RNA Design:
Target early exons (exons 1-5) or the serine-lipase domain (located within exons 10-14)
Design multiple gRNAs using tools like CHOPCHOP, CRISPOR, or Benchling
Select gRNAs with high on-target and low off-target scores
Example targets: conserved catalytic residues in the serine-lipase domain
Delivery Methods:
For cell lines: lipofection, electroporation, or lentiviral vectors
For animal models: embryo microinjection or electroporation
Validation of Knockout Efficiency:
| Validation Method | Technique | Expected Outcome |
|---|---|---|
| Genomic Validation | PCR + Sanger sequencing | Confirm indel mutations at target site |
| mRNA Expression | RT-qPCR | Reduced/absent SERAC1 transcript |
| Protein Detection | Western blot | Absence of SERAC1 protein |
| Functional Validation | Phospholipid ratio analysis | Increased PG-34:1/PG-36:1 ratio |
| Phenotypic Confirmation | mtDNA quantification | Reduced mtDNA content |
Controls:
Include wild-type controls
Generate heterozygous models as intermediate phenotype controls
Create rescue models by reintroducing wild-type SERAC1
Phenotypic Characterization:
Research has established that SERAC1 deficiency impairs mitochondrial function through disruption of phospholipid remodeling and nucleotide supply . The following protocols are recommended:
Oxygen consumption measurement using Seahorse XF Analyzer
Parameters to assess:
Basal respiration
ATP-linked respiration
Maximal respiratory capacity
Spare respiratory capacity
Proton leak
Quantitative PCR comparing mitochondrial to nuclear DNA ratio
Primers targeting conserved mtDNA regions and single-copy nuclear genes
Calculate relative mtDNA content using the 2^-ΔΔCt^ method
JC-1 or TMRM staining followed by flow cytometry or confocal microscopy
Analyze distribution patterns in different cellular compartments
Live-cell imaging using MitoTracker dyes
Transmission electron microscopy for ultrastructural analysis
Quantify parameters like mitochondrial number, size, and cristae density
Lipidomics approach using LC-MS/MS
Analyze cardiolipin species profile and content
Compare phosphatidylglycerol species ratios (PG-34:1/PG-36:1)
Measure serine transport into isolated mitochondria
Analyze flux through one-carbon cycle using isotope-labeled precursors
Quantify nucleotide pools in mitochondrial and cytosolic fractions
Nucleoside/nucleotide supplementation:
Gene complementation with wild-type SERAC1
Recent research has identified potential therapeutic strategies for SERAC1-related disorders, with nucleotide supplementation showing promising results:
Nucleoside/Nucleotide Supplementation:
Gene Therapy Approaches:
Viral vector-mediated gene delivery (AAV vectors)
Targeted to affected tissues (brain, liver, cochlea)
Mitochondrial-Targeted Therapies:
Compounds that enhance mitochondrial function (CoQ10, riboflavin)
Antioxidants to reduce oxidative stress resulting from mitochondrial dysfunction
Biochemical Markers:
3-methylglutaconic acid levels in urine
Lactate levels in blood and CSF
PG-34:1/PG-36:1 ratio in tissues and cultured cells
mtDNA content in tissues and blood
Functional Assays:
Mitochondrial respiratory chain activity
ATP production capacity
Mitochondrial membrane potential
Serine transport efficiency
Clinical Parameters:
Neurological function assessment
Hearing tests
Liver function tests
Growth and developmental parameters
Experimental Design for Therapeutic Testing:
| Study Phase | Model System | Outcome Measures | Duration |
|---|---|---|---|
| Preclinical | Cell models | mtDNA content, mitochondrial function | 1-4 weeks |
| Preclinical | Mouse models | Tissue-specific biomarkers, behavioral tests | 4-12 weeks |
| Clinical | Patient trials | Clinical parameters, biochemical markers | 6-24 months |
Research has shown that MEGD(H)EL syndrome shares molecular features with mtDNA depletion syndrome, suggesting that therapeutic approaches developed for mtDNA depletion disorders may be applicable to SERAC1-related conditions .
Distinguishing primary from secondary effects of SERAC1 dysfunction is crucial for understanding disease mechanisms and developing targeted therapies:
Temporal Analysis:
Conduct time-course experiments to establish the sequence of cellular and biochemical changes
Primary effects occur earlier, while secondary effects develop progressively
Monitor parameters at different time points following SERAC1 knockout or knockdown
Direct Target Identification:
Rescue Experiments:
Multi-omics Integration:
Compare transcriptomic, proteomic, and metabolomic changes
Map altered pathways to known SERAC1 functions
Use network analysis to distinguish hub effects from peripheral consequences
Single-Cell Analysis:
Examine cell-to-cell variability in response to SERAC1 deficiency
Identify cell populations most sensitive to primary SERAC1 function
Mitochondrial respiratory chain dysfunction
Elevated lactate and 3-methylglutaconic acid
Neurological symptoms
Hearing loss