Recombinant Mouse GDP-Man:Man (3)GlcNAc (2)-PP-Dol alpha-1,2-mannosyltransferase (Alg11)

Basic Research Questions

• What is the functional role of ALG11 in the N-glycan biosynthesis pathway?

  ALG11 functions as a GDP-Man:Man3GlcNAc2-PP-dolichol-alpha1,2-mannosyltransferase that catalyzes two sequential mannosylation reactions in the early stages of the lipid-linked oligosaccharide (LLO) biosynthesis pathway. Specifically, ALG11 transfers the fourth and fifth mannose residues from GDP-mannose (GDP-Man) to Man3GlcNAc2-PP-dolichol and Man4GlcNAc2-PP-dolichol, respectively, resulting in the production of Man5GlcNAc2-PP-dolichol .

  This enzymatic activity occurs on the cytosolic side of the endoplasmic reticulum (ER) membrane as part of the N-glycan precursor synthesis before the LLO flips into the ER lumen for further processing. ALG11 is categorized as part of two major biochemical pathways:

  Pathway Name	Related Proteins
  N-Glycan biosynthesis	RABGNT1, DOLPP1, ST6GAL1, DPM3, ZNF408, ALG12, ST6GAL2A, RPN1, MAN1A1, MGAT4B
  Metabolic pathways	UGT1A4, PFKMA, GCNT2, SUCLG2, ATP6AP1, GALNT18A, DAO.1, CBR1, GMPS, PIK3C2G

  Importantly, the sequential action of ALG11 is essential for the proper assembly of the LLO precursor, which ultimately affects the subsequent steps in protein N-glycosylation .

• What experimental techniques can be used to assess ALG11 enzyme activity?

  To assess ALG11 enzyme activity, researchers should implement a multi-faceted experimental approach:

  1. In vitro mannosyltransferase assays:

     • Use purified recombinant ALG11 protein (available as His-tagged constructs)

     • Employ radiolabeled GDP-[14C]mannose as the donor substrate

     • Use synthetic or isolated Man3GlcNAc2-PP-dolichol as the acceptor substrate

     • Detect product formation by thin-layer chromatography (TLC) or HPLC analysis

  2. Lipid-linked oligosaccharide (LLO) analysis:

     • Extract LLOs from cells expressing wild-type or mutant ALG11

     • Release oligosaccharides from dolichol by mild acid hydrolysis

     • Label released oligosaccharides with a fluorescent tag

     • Analyze by HPLC or mass spectrometry to detect accumulation of Man3GlcNAc2 and Man4GlcNAc2 intermediates

  3. Transferrin glycosylation analysis:

     • Analyze serum transferrin by isoelectric focusing or mass spectrometry

     • Determine glycoform patterns characteristic of ALG11 deficiency

     • Note: Some ALG11-CDG patients may show normal transferrin patterns, requiring additional biomarkers

  4. GP130 biomarker analysis:

     • Analyze cellular GP130 glycoforms by Western blotting

     • Compare migration patterns with known ALG11-CDG samples

     • This novel biomarker has proven useful in cases where transferrin analysis yields normal results

• How should I design expression systems for recombinant mouse ALG11 production?

  When designing expression systems for recombinant mouse ALG11 production, consider the following methodological guidelines:

  1. Expression vector selection:

     • For bacterial expression: Use pET-based vectors with N-terminal His-tag for E. coli expression systems

     • For mammalian expression: Consider pcDNA or pCMV vectors with appropriate signal sequences

  2. Expression host considerations:

     • E. coli: Suitable for producing soluble domains but may lack proper folding for full-length protein

     • Mammalian cells (HEK293): Preferable for full-length protein with proper folding and post-translational modifications

     • Insect cells: Alternative for membrane protein expression

  3. Protein sequence optimization:

     • The full-length mouse ALG11 protein consists of 492 amino acids

     • Consider the amino acid sequence: MAADTGSWCVYAVLRFFYSLFFPGLMICGVLCVYLVIGLWVIRWHLQRKKKSVSTSKNGKEQTVVAFFHPYCNAGGGGERVLWCALRALQKKYPEAVYVVYTGDINVSGQQILDGAFRRF... (as detailed in search result )

     • For optimal expression, remove transmembrane domains for soluble constructs

  4. Purification strategy:

     • Use Ni-sepharose affinity chromatography for His-tagged constructs

     • Implement size exclusion chromatography as a polishing step

     • Consider addition of mild detergents for membrane-bound forms

     • Stabilize with 6% trehalose in Tris/PBS-based buffer at pH 8.0

  5. Quality control:

     • Verify purity by SDS-PAGE (should exceed 90%)

     • Confirm identity by mass spectrometry

     • Test enzymatic activity using mannosyltransferase assays

• What cell models are appropriate for studying ALG11 function?

  When selecting cell models to study ALG11 function, researchers should consider these methodological approaches:

  1. Fibroblast models:

     • Primary fibroblasts from ALG11-CDG patients provide authentic disease models

     • Control fibroblasts can be genetically modified using CRISPR/Cas9 to introduce ALG11 mutations

     • Advantages: Maintain endogenous regulatory elements and expression levels

     • Analyze glycosylation profiles using GP130 as a biomarker

  2. Established cell lines:

     • HEK293 cells: Useful for overexpression studies and protein production

     • CHO-Lec cells: Glycosylation mutant cells that can be complemented with ALG11

     • Mouse embryonic fibroblasts (MEFs): Can be derived from ALG11-knockout models

  3. Yeast models:

     • S. cerevisiae alg11 mutants: Valuable for structure-function studies

     • Complementation assays with mouse/human ALG11 to assess functional conservation

     • Advantages: Simpler glycosylation pathway, easier genetic manipulation

  4. Neuronal models:

     • Induced Pluripotent Stem Cell (iPSC)-derived neurons from patient samples

     • Useful for studying neurological manifestations of ALG11-CDG

     • Enables investigation of cell-type specific effects of ALG11 deficiency

  5. Experimental validation:

     • Confirm ALG11 expression levels by Western blot

     • Verify subcellular localization to the ER membrane by immunofluorescence

     • Assess glycosylation status of specific glycoproteins by lectin blotting

Advanced Research Questions

• How can I design experiments to validate novel ALG11 variants for pathogenicity assessment?

  To validate novel ALG11 variants and assess their pathogenicity, implement this comprehensive experimental framework:

  1. In silico analysis pipeline:

     • Use mutation prediction tools (MutationTaster, CADD, PolyPhen)

     • Assess conservation scores across species

     • Model structural impacts using PyMol and FoldX for free energy changes

     • Example: The c.127T>C p.L46P variant had a CADD score of 26.8, placing it in the top 0.5% of deleterious variants

  2. Genomic and transcript analysis:

     • Sequence gDNA to identify variants

     • Amplify cDNA transcripts to identify non-functional alternative splicing

     • Design primers to capture intronic variants that may affect splicing

     • Example methodology: The c.208+25G>T variant was confirmed to cause non-functional alternative splicing

  3. Functional complementation studies:

     • Express wild-type and mutant ALG11 in ALG11-deficient cells

     • Assess rescue of glycosylation profile

     • Measure Man5GlcNAc2-PP-dolichol production

  4. Biochemical validation:

     • LLO analysis to detect accumulation of truncated precursors

     • Western blot analysis of GP130 glycoforms

     • Transferrin glycosylation profile (noting some ALG11-CDG patients show normal profiles)

     • Enzyme activity assays with purified proteins

  5. Cell-based validation framework:

     Experimental Approach	Methodology	Expected Result for Pathogenic Variants
     Protein expression	Western blot	Normal or reduced protein levels
     LLO analysis	HPLC/MS of extracted LLOs	Accumulation of Man3/Man4GlcNAc2 intermediates
     GP130 biomarker	Western blot	Aberrant GP130 glycoforms
     Transferrin analysis	ESI-MS	May be normal or show type I pattern
     Enzyme activity	In vitro assay	Reduced mannosyltransferase activity

  This multi-tiered approach provides robust evidence for variant pathogenicity, particularly important for variants of uncertain significance (VUS) .

• What experimental designs are most effective for investigating genotype-phenotype correlations in ALG11-CDG?

  To effectively investigate genotype-phenotype correlations in ALG11-CDG, implement the following experimental design approach:

  1. Patient cohort stratification:

     • Categorize patients into "severe" and "mild" phenotypic groups

     • Document comprehensive clinical features including:

       • Neurological manifestations (epilepsy, development)

       • Dysmorphic features

       • Visual impairments

       • Gastrointestinal symptoms

       • Survival outcomes

  2. Variant impact analysis:

     • Map variants to ALG11 protein domains

     • Classify variants based on molecular consequences:

       • Null variants (deletions, nonsense, frameshift)

       • Missense variants in conserved regions

       • Splicing variants

     • Example finding: Homozygous c.773C>T is associated with severe phenotype; when heterozygous with another variant in conserved regions (c.866A>T, c.1025A>C, c.1182C>G), patients show more severe phenotypes than variants in less-conserved regions (c.434G>A, c.450C>G, c.765G>A, c.1287T>A)

  3. Functional characterization methodology:

     • Generate patient-derived fibroblasts for each genotype

     • Create isogenic cell lines using CRISPR/Cas9 to isolate variant effects

     • Measure enzymatic activity as percentage of wild-type function

     • Quantify LLO intermediates

  4. Statistical approach:

     • Perform multivariate analysis to correlate specific symptoms with variant types

     • Calculate disease severity scores

     • Use regression models to identify predictive genetic factors

  5. Clinical feature correlation analysis:

     Clinical Feature	Incidence in Severe Phenotype	Incidence in Mild Phenotype	Statistical Significance
     Congenital nephrotic syndrome	Significantly higher	Lower	p<0.05
     Agammaglobulinemia	Significantly higher	Lower	p<0.05
     Severe hydrops	Significantly higher	Lower	p<0.05
     Intellectual disability	Universal	Universal	Not significant
     Epilepsy	Universal	Universal	Not significant
     Visual problems	Nearly universal	Common	Not significant

  This systematic approach enables correlation of specific genetic variants with clinical severity, facilitating better prediction of disease course and potential therapeutic approaches .

• How should I design experiments to investigate the interaction of ALG11 with other components of the dolichol pathway?

  To investigate ALG11 interactions with other components of the dolichol pathway, employ this multi-technique experimental design:

  1. Protein-protein interaction studies:

     • Proximity labeling techniques (BioID/APEX)

       • Express ALG11-BioID fusion in cells

       • Identify neighboring proteins by streptavidin pulldown and mass spectrometry

     • Co-immunoprecipitation

       • Use anti-ALG11 antibodies to pull down complexes

       • Identify partners by mass spectrometry

     • Yeast two-hybrid screening

       • Use cytosolic domains of ALG11 as bait

       • Screen against cDNA libraries from relevant tissues

  2. Subcellular localization and co-localization:

     • Confocal microscopy with fluorescently tagged proteins

     • Super-resolution techniques (STED, STORM) for nanoscale organization

     • Focus on potential interactions with preceding enzyme ALG2 and subsequent pathway components

  3. Functional interdependence analysis:

     • Genetic interaction studies

       • Create single and double knockdowns of ALG11 with other pathway enzymes

       • Compare phenotypic severity to identify synthetic lethality or rescue

     • Metabolic flux analysis

       • Trace mannose incorporation using isotope labeling

       • Measure pathway intermediates with mass spectrometry

  4. Membrane organization studies:

     • Lipid raft association analysis

     • Detergent resistance membrane fractionation

     • Identify co-fractionating proteins

  5. Pathway reconstitution:

     • In vitro reconstitution with purified components

     • Sequential enzyme assays to measure cooperative activity

     • Example model system: Use recombinant ALG11 and potential interactors expressed in E. coli

  6. Interactome mapping:

     Potential Interactor	Technique	Functional Relationship
     ALG2	Co-IP, Proximity labeling	Provides Man3GlcNAc2-PP-Dol substrate
     ALG3	Membrane fractionation	Accepts Man5GlcNAc2-PP-Dol product
     RFT1	Genetic interaction	Flips LLO into ER lumen
     Dolichol-P-Man synthase	Metabolic flux analysis	Provides GDP-Man substrate

  By implementing this comprehensive approach, researchers can elucidate the physical and functional interactions of ALG11 within the complex dolichol pathway, providing insights into the coordinated process of LLO synthesis .

• What methodological approaches can resolve contradictory findings about ALG11 function in different experimental systems?

  To resolve contradictory findings about ALG11 function across different experimental systems, implement this systematic methodological framework:

  1. Standardized experimental conditions:

     • Establish consistent protocols for ALG11 activity assays

     • Define standard buffer conditions, substrate concentrations, and temperature

     • Use recombinant proteins with identical tags and purification methods

     • Compare E. coli-expressed versus mammalian cell-expressed ALG11 to assess post-translational modifications' influence

  2. Multi-model validation approach:

     • Test hypotheses across multiple systems:

       • Yeast complementation

       • Mammalian cell models

       • Cell-free enzymatic assays

       • Patient-derived materials

     • Document discrepancies systematically

     • Identify system-specific factors that may influence results

  3. Contradiction resolution framework:

     • Characterize specific points of contradiction

     • Design critical experiments targeting these specific discrepancies

     • Implement controlled variable testing by changing only one parameter at a time

     • Example contradiction: Normal transferrin glycosylation in some ALG11-CDG patients despite cellular glycosylation defects

  4. Technical validation controls:

     • Include positive and negative controls in all experiments

     • Verify ALG11 expression levels and localization in each system

     • Use multiple detection methods for key outcomes

     • Cross-validate findings using orthogonal techniques

  5. Data integration and meta-analysis:

     • Systematically review published literature

     • Compile contradictory findings in structured format

     • Identify patterns in experimental conditions that correlate with outcomes

     • Develop unified models that accommodate seemingly contradictory results

  6. Contradiction analysis table:

     Contradictory Finding	Possible Explanation	Resolution Approach
     Normal vs. abnormal transferrin patterns	Tissue-specific compensation mechanisms	Compare multiple glycoprotein markers across tissues
     Variable phenotypic severity with similar variants	Genetic modifiers or environmental factors	Whole genome/exome sequencing to identify modifiers
     Discrepant enzyme activity in vitro vs. in vivo	Missing cofactors or membrane environment	Reconstitute activity in membrane-mimetic systems
     Differences between mouse and human ALG11	Species-specific protein interactions	Cross-species complementation experiments

  By systematically addressing contradictions through this structured approach, researchers can develop a more complete and accurate understanding of ALG11 function across different biological contexts .

• How can I design experimental protocols to differentiate between ALG11-CDG and other disorders of glycosylation in research samples?

  To differentiate between ALG11-CDG and other disorders of glycosylation in research samples, implement this comprehensive diagnostic protocol:

  1. Tiered biochemical analysis approach:

     • First-line screening:

       • Serum transferrin analysis by mass spectrometry (ESI-MS)

       • Identify type I pattern (reduced glycan occupancy)

       • Note: ALG11-CDG may occasionally show normal patterns

     • Second-line confirmatory tests:

       • LLO analysis from patient fibroblasts

       • Characteristic finding: Accumulation of Man3GlcNAc2-PP-Dol and Man4GlcNAc2-PP-Dol

       • Compare with patterns for other CDGs (e.g., ALG1-CDG shows N2M1/2 accumulation)

  2. Novel biomarker analysis:

     • GP130 Western blot analysis:

       • Extract proteins from fibroblasts

       • Perform Western blot for GP130

       • Compare migration patterns with known ALG11-CDG samples

       • Specific pattern: Truncated GP130 isoforms characteristic of ALG11 deficiency

  3. Genetic analysis pipeline:

     • Targeted gene panel:

       • Sequence ALG11 and other N-glycosylation pathway genes

       • Look for biallelic variants in ALG11

     • Complementation assays:

       • Express wild-type ALG11 in patient fibroblasts

       • Assess rescue of glycosylation phenotype

     • Copy number variation (CNV) analysis:

       • Check for ALG11 deletions/duplications

       • Example finding: Patient with paternal ALG11 deletion and maternal missense variant

  4. Differential features table:

     Diagnostic Feature	ALG11-CDG	ALG1-CDG	ALG2-CDG	PMM2-CDG
     LLO accumulation	Man3/4GlcNAc2	N2M1/2	Man1GlcNAc2	Normal LLO
     Transferrin pattern	Type I pattern (may be normal)	Type I pattern	Type I pattern	Type I pattern
     GP130 glycoforms	Specific truncated pattern	Different pattern	Different pattern	Different pattern
     Enzyme assay	↓ Man3→Man5 activity	↓ GlcNAc→Man1 activity	↓ Man1→Man3 activity	↓ PMM2 activity

  5. Clinical correlation:

     • Document key phenotypic features:

       • Universal features: Intellectual disability, epilepsy

       • Common features: Visual problems, hypotonia, dysmorphism

       • Distinctive features: Severity varies by genotype

  This systematic differential diagnostic approach enables accurate identification of ALG11-CDG and distinguishes it from other disorders of glycosylation, which is critical for research sample classification and subsequent analyses .

• What are the most rigorous experimental designs for testing potential therapeutic approaches targeting ALG11 deficiency?

  To test potential therapeutic approaches for ALG11 deficiency, implement this rigorous experimental design framework:

  1. Cell-based screening platform:

     • Establish ALG11-deficient cell models:

       • Patient-derived fibroblasts with confirmed ALG11 mutations

       • CRISPR-engineered cell lines with specific ALG11 variants

       • ALG11-knockout cells complemented with mutant ALG11

     • Define clear readouts:

       • GP130 glycosylation pattern normalization

       • LLO profile restoration

       • Functional glycoprotein assays

  2. Therapeutic approach categories:

     • Gene therapy/gene editing:

       • AAV-mediated ALG11 gene delivery

       • CRISPR-based correction of ALG11 mutations

       • Methodology: Test different viral serotypes for tissue-specific delivery

     • Small molecule screening:

       • Man3GlcNAc2-PP-dolichol analogs as alternative substrates

       • Chaperones to stabilize mutant ALG11 proteins

       • ER stress modulators

     • Metabolic bypass strategies:

       • Mannose supplementation at various concentrations

       • Dolichol-phosphate-mannose synthetic pathway enhancement

  3. Experimental design principles:

     • Include appropriate controls:

       • Wild-type cells

       • Vehicle-treated ALG11-deficient cells

       • Positive control (genetic complementation with wild-type ALG11)

     • Implement randomization and blinding:

       • Randomly assign treatment conditions

       • Blind analysis of outcome measures

     • Apply rigorous statistical approach:

       • Power analysis to determine sample size

       • Multiple testing correction

       • Reproducibility across independent experiments

  4. Multi-phase testing protocol:

     Phase	Methodology	Endpoints	Success Criteria
     1. In vitro screening	High-throughput cell-based assays	GP130 glycosylation, cell viability	≥50% restoration of glycosylation
     2. Mechanism validation	Metabolic labeling, enzyme assays	Pathway flux, ALG11 activity	Confirmed target engagement
     3. Disease model testing	Patient-derived fibroblasts, iPSC-neurons	Tissue-specific glycoprotein function	Functional improvement in disease-relevant cells
     4. Pre-clinical animal studies	ALG11-deficient mouse model	Survival, neurological function	Improved phenotype, safety

  5. Translational considerations:

     • Therapeutic window assessment

     • Tissue-specific delivery strategies

     • Duration of treatment effect

     • Combinatorial approaches for synergistic effects

  This comprehensive experimental framework provides a rigorous approach to therapeutic development for ALG11 deficiency, with clear go/no-go decision points and translational pathways .

• How can I develop an ALG11 knockout mouse model and what experimental controls should be included?

  To develop and characterize an ALG11 knockout mouse model with appropriate experimental controls, follow this comprehensive methodological framework:

  1. Knockout strategy design:

     • Complete knockout approach:

       • Target critical exons (e.g., those encoding catalytic domains)

       • Consider that complete ALG11 knockout may be embryonic lethal

     • Conditional knockout approach:

       • Implement Cre-loxP system for tissue-specific deletion

       • Create floxed ALG11 allele targeting critical exons

       • Select tissue-specific Cre lines relevant to CDG phenotypes (brain, liver)

     • Knockin approach for specific mutations:

       • CRISPR/Cas9-mediated introduction of patient-specific mutations

       • Target confirmed pathogenic variants (e.g., c.773C>T)

  2. Genotyping and validation strategy:

     • PCR-based genotyping protocols

     • RT-PCR and Western blot to confirm reduced/absent expression

     • Enzymatic assays to confirm functional deficiency

     • LLO analysis to verify biochemical phenotype

  3. Essential experimental controls:

     • Genetic controls:

       • Wild-type littermates (+/+)

       • Heterozygous mice (+/-) to assess dosage effects

       • Tissue-specific knockout controls (Cre-only mice)

     • Rescue controls:

       • Transgenic ALG11 expression on knockout background

       • Tissue-specific rescue to define critical tissues

     • Background strain controls:

       • Backcross to multiple backgrounds to assess modifier effects

       • Use littermate controls to minimize background effects

  4. Phenotypic characterization protocol:

     • Developmental assessment:

       • Embryonic development timeline

       • Survival rates

       • Growth curves

     • Biochemical profiling:

       • Glycoprotein analysis in multiple tissues

       • N-glycan profiling by mass spectrometry

       • Tissue-specific glycosylation defects

     • Neurological assessment:

       • Behavioral testing battery

       • EEG for seizure susceptibility

       • Neuroimaging

  5. Experimental design considerations:

     Experimental Aspect	Methodology	Controls	Expected Outcomes
     Embryonic lethality assessment	Timed pregnancies, genotyping of embryos	Mendelian ratios	Potential early lethality of homozygous knockouts
     Tissue-specific phenotypes	Conditional knockouts in brain, liver, etc.	Cre-only mice, floxed-only mice	Tissue-specific glycosylation defects
     Biochemical characterization	LLO analysis, glycoprotein testing	Wild-type, heterozygous tissues	Accumulation of Man3/4GlcNAc2-PP-Dol intermediates
     Therapeutic testing	Mannose supplementation, gene therapy	Vehicle-treated knockout mice	Rescue of phenotypes

  6. Translational application:

     • Preclinical testing of therapeutic approaches

     • Biomarker validation

     • Age-dependent phenotype progression

  This comprehensive approach ensures the development of a well-controlled and physiologically relevant ALG11 knockout mouse model that can be used to understand disease mechanisms and test therapeutic strategies .

• What experimental approaches can be used to investigate the tissue-specific effects of ALG11 deficiency?

  To investigate tissue-specific effects of ALG11 deficiency, implement this comprehensive experimental framework:

  1. Tissue-specific conditional knockout models:

     • Generate ALG11-floxed mice and cross with tissue-specific Cre lines:

       • Nestin-Cre for nervous system

       • Albumin-Cre for hepatocytes

       • Ksp-Cre for kidney

       • MHC-Cre for cardiac tissue

     • Validate tissue-specific deletion by:

       • RT-PCR and Western blot analysis

       • Immunohistochemistry

       • Tissue-specific enzymatic activity

  2. Human tissue sampling approach:

     • Analyze available tissues from ALG11-CDG patients:

       • Skin fibroblasts (most accessible)

       • Blood samples for immune cell analysis

       • When available: biopsy samples from affected organs

     • iPSC-derived models:

       • Generate iPSCs from patient fibroblasts

       • Differentiate into multiple lineages (neurons, hepatocytes, cardiomyocytes)

       • Compare glycosylation profiles across lineages

  3. Comprehensive glycoprotein analysis:

     • Tissue glycoproteomics:

       • Extract proteins from specific tissues

       • Enrich for glycoproteins using lectin affinity

       • Mass spectrometry analysis of glycopeptides

     • Targeted analysis of tissue-specific glycoproteins:

       • Neural: Neural cell adhesion molecule (NCAM)

       • Liver: Alpha-1-antitrypsin, transferrin

       • Kidney: Podocalyxin

       • Evaluate site occupancy and glycan structures

  4. Functional consequence assessment:

     • Tissue-specific cellular phenotypes:

       • Neuron: Synaptogenesis, electrophysiology

       • Hepatocytes: Protein secretion, metabolic function

       • Kidney cells: Filtration barrier integrity

     • Intercellular communication:

       • Cell-cell adhesion assays

       • Migration and invasion assays

       • Extracellular matrix interactions

  5. Comparative tissue analysis:

     Tissue	Glycoprotein Markers	Functional Assays	Expected Phenotype in ALG11 Deficiency
     Brain	NCAM, synaptic proteins	Electrophysiology, neurite outgrowth	Impaired synaptogenesis, altered neuronal migration
     Liver	Transferrin, coagulation factors	Protein secretion assays	Reduced glycoprotein secretion, coagulopathy
     Kidney	Podocalyxin, nephrin	Filtration assays	Potential proteinuria, filtration defects
     Muscle	Dystroglycan	Muscle fiber integrity	Potential myopathy, reduced glycoprotein stability
     Eye	Rhodopsin, crystallins	Visual function tests	Retinal degeneration, visual impairment

  6. Developmental timeline analysis:

     • Embryonic tissue collection at multiple timepoints

     • Postnatal developmental stages

     • Adult and aging analysis

     • Correlate with clinical progression in patients

  This multi-faceted approach allows for comprehensive characterization of tissue-specific consequences of ALG11 deficiency, providing insights into the pathophysiological mechanisms underlying the multiple organ involvement in ALG11-CDG .