Recombinant Human Atlastin-1 (ATL1)

What is Atlastin-1 and what is its primary function in cellular biology?

Atlastin-1 is a dynamin-like GTPase encoded by the ATL1 gene that plays a crucial role in endoplasmic reticulum (ER) membrane fusion and tubular network formation. It functions primarily in endoplasmic reticulum tubular network biogenesis by tethering membranes through the formation of trans-homooligomers, mediating homotypic fusion of ER membranes . This protein belongs to the GBP family, Atlastin subfamily, and contains characteristic GTPase domains essential for its function . Recent research demonstrates that ATL1 is required for correct ER morphology in human neurons, particularly in forming the three-way junctions that characterize ER networks .

What are the key structural domains of Atlastin-1 and how do they contribute to its function?

Atlastin-1 contains several key structural domains that enable its membrane fusion activity:

• GTPase (G) domain: A canonical large GTPase domain characteristic of the dynamin superfamily that provides the energy required for membrane fusion through GTP hydrolysis .

• Middle domain: Functions as a stalk-like structure that is critical for proper protein conformation and activity. Mutations in this domain, such as the N417ins insertion mutation, can significantly impact protein function .

• Transmembrane domains: These anchor the protein to the ER membrane and are essential for its localization and function .

• Cytoplasmic domain: Involved in protein-protein interactions and oligomerization necessary for membrane tethering and fusion .

The coordinated function of these domains enables ATL1 to bind GTP, dimerize, undergo conformational changes, and bring ER membranes together for fusion, which is critical for maintaining the characteristic tubular morphology of the ER network.

How does Atlastin-1 interact with other proteins in the endoplasmic reticulum?

Atlastin-1 engages in several protein-protein interactions within the endoplasmic reticulum network:

• Self-interaction: ATL1 forms homooligomers essential for its membrane tethering and fusion activities .

• Interaction with ER-shaping proteins: Research shows functional relationships between ATL1 and other proteins involved in ER morphology, including spastin (SPAST), REEP1, NIPA1, and ZFYVE27 . These interactions form part of a complex network regulating ER shape and function.

• Golgi apparatus interactions: ATL1 may also regulate Golgi biogenesis, suggesting interactions with Golgi-resident proteins .

These interactions collectively contribute to the maintenance of ER morphology and function, with disruptions potentially leading to neurodegenerative conditions like hereditary spastic paraplegia.

What genetic mutations in ATL1 are associated with hereditary spastic paraplegia, and how do they affect protein function?

Mutations in the ATL1 gene are among the most common causes of hereditary spastic paraplegia (HSP), particularly autosomal dominant HSP type 3 (SPG3A) . Over 68 HSP-causing mutations have been identified in ATL1, with the majority being autosomal dominant and resulting in early onset cases .

These mutations affect ATL1 function in several ways:

• GTPase domain mutations: Can impair GTP binding or hydrolysis, preventing the energy-dependent conformational changes necessary for membrane fusion.

• Middle domain mutations: The novel insertion mutation (N417ins) between arginine residue 416 and tyrosine residue 417 has been associated with early onset, complex HSP featuring spastic quadriplegia, generalized dystonia, and thinning of the corpus callosum .

• Transmembrane domain mutations: May disrupt proper localization to the ER membrane or alter membrane interaction properties.

The resulting dysfunctional ATL1 leads to abnormal ER morphology, particularly affecting the formation of three-way junctions in the tubular ER network . This ultimately contributes to axonal degeneration of corticospinal tract axons, the hallmark pathology of HSP.

How does ATL1 dysfunction contribute to neurodegenerative processes beyond ER morphology defects?

Recent research has revealed that ATL1 dysfunction extends beyond direct effects on ER morphology, influencing additional cellular processes critical for neuronal health:

• Endosomal tubulation: Neurons lacking ATL1 display longer endosomal tubules, suggesting defective tubule fission mechanisms . This abnormal endosomal morphology may impair proper endosomal trafficking and sorting.

• Reduced lysosomal proteolytic capacity: ATL1 deficiency leads to decreased lysosomal proteolytic function . This finding strengthens the hypothesis that defective lysosome function contributes to the pathogenesis of various forms of HSP, even when the mutated protein primarily localizes outside the endolysosomal system.

• Axonal development: ATL1 may regulate axonal development, with mutations potentially disrupting proper axon formation and maintenance .

These diverse mechanisms suggest that ATL1-related neurodegeneration involves complex cellular pathway disruptions beyond simple ER morphology defects, potentially offering multiple therapeutic targets for intervention.

What is the relationship between ATL1 mutations and hereditary sensory neuropathy?

In addition to hereditary spastic paraplegia, defects in ATL1 are also the cause of hereditary sensory neuropathy type 1D (HSN1D) . This relationship highlights the diverse neurological consequences of ATL1 dysfunction:

• Clinical presentation: HSN1D is characterized by adult-onset distal axonal sensory neuropathy leading to mutilating ulcerations and hyporeflexia, with some patients showing features suggesting upper neuron involvement .

• Mechanistic overlap: The dual association of ATL1 with both HSP and HSN suggests shared pathogenic mechanisms, particularly regarding the vulnerability of long axons to ER dysfunction.

• Familial mutations: Mutations in both ATL1 and the related protein ATL3 have been found to cause HSN, indicating functional redundancy or parallel pathways within the atlastin family that affect sensory neurons .

This connection between ATL1 mutations and different neurodegenerative conditions underscores the critical role of ER morphology and function in maintaining neuronal health, particularly in cells with extensive processes such as sensory and motor neurons.

What are the most effective methods for expressing and purifying recombinant human ATL1 for structural and functional studies?

Effective expression and purification of recombinant human ATL1 requires specialized approaches due to its membrane protein nature:

• Expression systems:

  • Bacterial expression: E. coli systems are suitable for expressing soluble domains (e.g., the GTPase domain) but may require optimization of codon usage and growth conditions.

  • Eukaryotic expression: Insect cell (Sf9, High Five) or mammalian cell (HEK293, CHO) systems are preferred for full-length ATL1 to ensure proper folding and post-translational modifications.

• Purification strategies:

  • For membrane-bound full-length ATL1:

    • Gentle detergent solubilization (n-dodecyl-β-D-maltoside or digitonin)

    • Affinity chromatography using His-tags or GST-tags

    • Size exclusion chromatography for final purification

• Quality control:

  • GTPase activity assays to confirm functional integrity

  • Circular dichroism to assess proper folding

  • Dynamic light scattering to evaluate oligomeric state

For functional studies, reconstitution into liposomes or nanodiscs may be necessary to preserve native conformation and activity of this membrane-associated protein.

What are the recommended approaches for studying ATL1 membrane fusion activity in vitro?

Studying ATL1 membrane fusion activity requires specialized techniques that recapitulate its native environment:

• Liposome fusion assays:

  • Preparation of liposomes with lipid compositions mimicking the ER membrane

  • Incorporation of purified recombinant ATL1 into separate liposome populations

  • Monitoring fusion using fluorescence-based assays:

    • Lipid mixing assays (using fluorescent lipid pairs like NBD-PE and Rh-PE)

    • Content mixing assays (using self-quenching fluorophores)

• Microscopy-based approaches:

  • Reconstitution of ATL1 into GUVs (Giant Unilamellar Vesicles)

  • Direct visualization of fusion events using confocal or TIRF microscopy

  • Quantification of fusion kinetics and efficiency

• Biophysical characterization:

  • Surface plasmon resonance to study protein-membrane interactions

  • Stopped-flow techniques to measure kinetics of GTP hydrolysis coupled to conformational changes

  • Analytical ultracentrifugation to study oligomerization states

These methodologies allow for quantitative assessment of how disease-causing mutations affect the membrane fusion activity of ATL1, providing mechanistic insights into pathogenesis.

How can CRISPR-based approaches be used to study ATL1 function in neuronal models?

CRISPR technology offers powerful approaches for studying ATL1 function in relevant neuronal models:

• CRISPR inhibition (CRISPRi):

  • As demonstrated in recent research, CRISPRi can be used to generate human cortical neurons lacking atlastin-1

  • This approach allows for specific knockdown of ATL1 without complete gene deletion

  • Advantages include temporal control and reduced off-target effects compared to traditional knockout methods

• CRISPR activation (CRISPRa):

  • Can be used to upregulate ATL1 expression to study gain-of-function effects

  • Useful for examining dose-dependent effects of ATL1 on ER morphology

• CRISPR-mediated knock-in:

  • Introduction of specific disease-associated mutations (such as the N417ins insertion)

  • Generation of isogenic cell lines that differ only in ATL1 status

  • Particularly valuable for studying the effects of patient-specific mutations

• Experimental design considerations:

  • For neuronal studies, iPSC-derived neurons or directly reprogrammed neurons provide human-relevant models

  • Implementation of inducible systems allows for temporal control of genetic modifications

  • Inclusion of appropriate controls (non-targeting gRNAs, rescue experiments)

These CRISPR-based approaches facilitate detailed investigation of ATL1 function in human neurons, as demonstrated by studies showing altered ER morphology, endosomal tubulation, and lysosomal proteolytic capacity in neurons lacking atlastin-1 .

How does ATL1 functionally interact with other HSP-associated proteins in maintaining neuronal health?

The functional interplay between ATL1 and other HSP-associated proteins forms a complex network crucial for neuronal maintenance:

• Protein interaction network:
  Several HSP-associated proteins show functional or physical interactions with ATL1:

  • SPAST (Spastin): Over 29 publications document interactions between ATL1 and SPAST

  • REEP1: At least 6 publications describe interactions between ATL1 and REEP1

  • NIPA1: Documented in more than 5 publications

  • ZFYVE27: At least 1 publication shows interaction with ATL1

  • KIAA0196: Reported in at least 1 publication

• Functional coordination:
  These proteins collectively maintain ER morphology, microtubule dynamics, and membrane trafficking pathways. Disruption of any component can lead to similar neuronal pathologies, suggesting functional redundancy or compensatory mechanisms.

• Convergent pathways:
  Recent research indicates that mutations in seemingly unrelated HSP genes ultimately lead to common downstream effects, including:

  • Disrupted endosomal tubulation

  • Impaired lysosomal proteolytic function

  • Altered axonal transport mechanisms

Understanding these interactions provides insight into why mutations in diverse proteins can produce similar clinical phenotypes and suggests potential for common therapeutic approaches across different genetic forms of HSP.

What is the relationship between ATL1 dysfunction and altered lysosomal proteolytic capacity in neurodegenerative disease?

Recent research has revealed an unexpected link between ATL1 dysfunction and lysosomal abnormalities:

• Experimental evidence:
  Human cortical neurons lacking atlastin-1 demonstrate:

  • Reduced lysosomal proteolytic capacity

  • Longer endosomal tubules, suggesting defective tubule fission

• Mechanistic connections:
  Several potential mechanisms may explain this relationship:

  • Disrupted ER-endosome membrane contact sites

  • Altered calcium signaling affecting endolysosomal function

  • Impaired trafficking of lysosomal enzymes from ER to lysosomes

  • Compromised autophagosome-lysosome fusion

• Broader implications:
  This finding strengthens the emerging concept that defective lysosome function contributes to the pathogenesis of multiple forms of HSP, even those where the primary protein localization is not at the endolysosomal system . This suggests a unifying mechanism across different genetic forms of HSP and potentially other neurodegenerative conditions.

This relationship demonstrates how primary defects in ER morphology can exert wide-ranging effects on other organelle systems, highlighting the interconnected nature of cellular homeostasis in neurons.

How do different ATL1 mutations differentially affect protein structure and function?

The diverse mutations in ATL1 associated with neurological disorders produce distinct effects on protein structure and function:

• Mutation classification and structural impacts:

  Mutation Type	Domain	Structural Effect	Functional Consequence
  Missense	GTPase	Altered GTP binding/hydrolysis	Reduced energy for conformational change
  Missense	Middle	Disrupted protein folding	Impaired dimerization
  Insertion (e.g., N417ins)	Middle	Altered conformation	Modified membrane tethering activity
  Transmembrane	TM domains	Mislocalization	Reduced membrane association
  Truncation	Various	Incomplete protein	Loss of function or dominant negative

• Genotype-phenotype correlations:
  Different mutations correlate with distinct clinical presentations:

  • The novel N417ins insertion mutation results in early onset, complex HSP with spastic quadriplegia and generalized dystonia

  • Some mutations produce pure HSP phenotypes

  • Others lead to hereditary sensory neuropathy type 1D

• Biochemical differences:
  Studies reveal that not all mutations disrupt protein stability; for example, the N417ins insertion mutant results in stable protein but with altered membrane tethering activity . This suggests that therapeutic approaches may need to be tailored to specific mutation types.

Understanding these differential effects is crucial for developing targeted therapeutic strategies and explaining the variation in clinical presentation among patients with different ATL1 mutations.

What imaging techniques and analytical methods are most appropriate for quantifying ER morphology defects in ATL1-deficient cells?

Accurate quantification of ER morphology in ATL1-deficient cells requires specialized imaging and analytical approaches:

• Advanced imaging techniques:

  • Super-resolution microscopy (STED, STORM, PALM): Provides nanoscale resolution of ER tubules and three-way junctions

  • Live-cell imaging: Captures dynamic ER remodeling events

  • Correlative light and electron microscopy (CLEM): Combines ultrastructural detail with protein localization

  • Focused ion beam-scanning electron microscopy (FIB-SEM): Enables 3D reconstruction of ER networks

• Quantitative metrics for ER morphology:

  • Three-way junction density: Critical parameter shown to be reduced in neurons lacking atlastin-1

  • Tubule length and diameter: Measures basic ER tubular structure

  • Network complexity: Graph theory-based analysis of connectivity

  • ER cisternal vs. tubular ratio: Indicates shift in ER subdomains

• Analytical software and approaches:

  • ImageJ/Fiji with specialized plugins: Analysis3D, ER-analyzer

  • MATLAB-based custom analysis: For automated detection of network features

  • Machine learning approaches: For unbiased classification of morphological patterns

• Statistical considerations:

  • Use of appropriate controls (non-targeting CRISPR, rescue experiments)

  • Analysis of sufficient cell numbers to account for natural variation

  • Blinded analysis to prevent observer bias

These approaches collectively enable quantitative assessment of how ATL1 deficiency affects ER network architecture, providing objective metrics for comparing different mutations or therapeutic interventions.

What experimental controls are essential when evaluating the effects of ATL1 mutations on neuronal function?

Rigorous control strategies are essential when studying the effects of ATL1 mutations:

• Genetic controls:

  • Isogenic cell lines: Using CRISPR-edited lines that differ only in ATL1 status

  • Rescue experiments: Re-expression of wild-type ATL1 to confirm specificity

  • Expression of multiple ATL1 mutants: To distinguish mutation-specific effects

  • Non-targeting CRISPR controls: For CRISPRi/CRISPRa experiments

• Cellular model controls:

  • Developmental stage matching: Ensuring neurons are at comparable maturation stages

  • Cell type specificity: Comparing effects in vulnerable vs. resistant neuronal types

  • Non-neuronal controls: Determining cell-type specificity of phenotypes

• Functional assays:

  • Positive controls: Known modulators of ER morphology or function

  • Multiple readouts: Assessing ER morphology, lysosomal function, and neuronal health

  • Temporal analysis: Distinguishing primary from secondary effects

• Methodological considerations:

  • Dose-dependence: Titrating expression levels of mutant proteins

  • Antibody validation: Confirming specificity of ATL1 detection

  • Blinded analysis: Preventing observer bias in quantification

How should researchers approach contradictory findings in the literature regarding ATL1 function?

When faced with contradictory findings regarding ATL1 function, researchers should employ a systematic approach:

• Methodological reconciliation:

  • Expression system differences: Bacterial vs. mammalian vs. in vitro systems

  • Protein construct variations: Full-length vs. truncated proteins

  • Assay sensitivity and specificity: Different techniques measure different aspects of function

  • Cell type considerations: Findings from non-neuronal cells may not translate to neurons

• Analytical framework for reconciliation:

  • Meta-analysis: Systematic review of methodologies and findings

  • Direct replication studies: Testing key contradictory findings under identical conditions

  • Collaborative approaches: Multi-laboratory validation of protocols

• Experimental design to resolve contradictions:

  • Mechanistic dissection: Identifying context-dependent factors that explain differences

  • Development of standardized assays: Creating field-wide accepted methodologies

  • Integration of multiple techniques: Combining structural, biochemical, and cellular approaches

• Interpretation guidelines:

  • Context-specificity: Recognizing that ATL1 may have different functions in different cellular contexts

  • Developmental considerations: Function may vary across neuronal maturation stages

  • Species differences: Human vs. rodent ATL1 might have subtle functional differences

When approaching the literature, researchers should consider these factors and design experiments that directly address contradictions, ultimately leading to a more nuanced understanding of ATL1 biology that accommodates seemingly disparate findings.

What therapeutic strategies targeting ATL1 dysfunction show the most promise for HSP and related disorders?

Several emerging therapeutic approaches targeting ATL1 dysfunction show potential:

• Gene therapy approaches:

  • AAV-mediated gene replacement: Delivery of functional ATL1 to affected neurons

  • CRISPR-based gene editing: Correction of specific mutations

  • Allele-specific silencing: For dominant mutations

• Small molecule interventions:

  • GTPase modulators: Compounds that enhance residual GTPase activity

  • Protein folding stabilizers: Chemical chaperones to improve stability of mutant proteins

  • ER stress reducers: Molecules targeting downstream consequences

• Cell-based therapies:

  • Stem cell transplantation: Replacement of affected neural populations

  • Exosome therapeutics: Delivery of functional ATL1 protein via exosomes

• Targeting downstream pathways:

  • Lysosomal enhancement therapies: Given the connection between ATL1 and lysosomal dysfunction

  • Microtubule stabilizers: To support axonal transport

  • Mitochondrial supportive therapies: Addressing energy deficits in affected neurons

The most promising approaches likely involve combinations of these strategies, tailored to specific mutation types and disease stages. Therapies targeting lysosomal function may have particular potential given recent findings connecting ATL1 dysfunction to reduced lysosomal proteolytic capacity .

How might advanced imaging techniques enhance our understanding of ATL1 dynamics in living neurons?

Advanced imaging techniques offer unprecedented opportunities to understand ATL1 function:

• Live super-resolution microscopy:

  • Tracking of individual ATL1 molecules during ER fusion events

  • Visualization of conformational changes using FRET-based biosensors

  • Mapping of ATL1 oligomerization dynamics during membrane fusion

• Advanced fluorescent protein applications:

  • Split-GFP approaches to monitor protein-protein interactions

  • Photoactivatable/photoswitchable fluorophores to track ATL1 mobility

  • FRAP (Fluorescence Recovery After Photobleaching) to measure protein dynamics

• Correlative microscopy approaches:

  • CLEM (Correlative Light and Electron Microscopy) to connect protein localization with ultrastructure

  • Integration with cryo-electron tomography for structural context

  • Volume EM techniques (FIB-SEM) for 3D reconstruction of entire neuronal processes

• Functional imaging:

  • Calcium imaging combined with ATL1 visualization

  • Measurement of membrane potential changes during ER remodeling

  • Simultaneous imaging of multiple organelles to track interorganelle contacts

These advanced techniques can reveal how ATL1 dynamics differ in disease-causing mutations, potentially identifying specific steps in the membrane fusion process that are compromised and revealing new therapeutic targets.

What are the most promising model systems for studying ATL1-related neurodegeneration?

Several model systems offer complementary advantages for studying ATL1-related neurodegeneration:

Recent research using CRISPRi in human cortical neurons has proven particularly valuable, revealing both ER morphology defects and unexpected consequences for endosomal tubulation and lysosomal function .

What are best practices for designing experiments to evaluate the effects of novel ATL1 mutations?

Rigorous experimental design is crucial when evaluating novel ATL1 mutations:

• Comprehensive mutation characterization:

  • Structural analysis: Computational modeling to predict effects on protein structure

  • Evolutionary conservation: Assessment of affected residues across species

  • Domain mapping: Determination of which functional domain is affected

  • Population frequency: Confirmation of rarity/absence in control populations

• Multi-level experimental approach:

  • Biochemical characterization: GTPase activity, protein stability, oligomerization

  • Cellular assays: ER morphology, membrane fusion capacity, protein localization

  • Neuronal phenotypes: Axon development, lysosomal function, electrophysiology

  • Systems level: Transcriptomic/proteomic changes, interactome alterations

• Model system selection:

  • Progressive complexity: From in vitro systems to cellular models to organisms

  • Isogenic backgrounds: CRISPR/Cas9 engineered cell lines with specific mutations

  • Patient-derived models: iPSC-neurons from affected individuals

• Controls and validation:

  • Known mutations: Comparison with well-characterized mutations

  • Rescue experiments: Complementation with wild-type ATL1

  • Structure-function correlations: Testing predictions with targeted mutations

  • Multiple methodologies: Confirming findings with complementary approaches

This systematic approach ensures thorough characterization of novel mutations like the recently identified N417ins insertion mutation, which produces a stable protein with altered membrane tethering activity associated with spastic quadriplegia .

How should researchers approach the development of high-throughput screens for ATL1 modulators?

Developing effective high-throughput screens for ATL1 modulators requires careful consideration of assay design:

• Primary assay selection:

  • GTPase activity assays: Colorimetric/fluorescent detection of phosphate release

  • Protein-protein interaction: FRET, AlphaScreen, or split-luciferase approaches

  • Membrane fusion assays: Fluorescent lipid mixing in reconstituted systems

  • ER morphology readouts: Automated image analysis of ER structure

• Assay optimization parameters:

  • Signal-to-noise ratio: Maximizing detection of true hits

  • Miniaturization: Adaptation to 384/1536-well formats

  • Robustness: Z'-factor assessment for assay quality

  • Scalability: Compatibility with automation platforms

• Compound library selection:

  • FDA-approved drug libraries: Potential for repurposing

  • Natural product collections: Novel chemical scaffolds

  • Focused libraries: Targeting GTPases or membrane protein modulators

  • Fragment libraries: Identifying starting points for medicinal chemistry

• Secondary assay cascade:

  • Confirmatory biochemical assays: Validate primary hits

  • Cellular phenotypic assays: ER morphology restoration in patient cells

  • Selectivity panels: Ensure specificity against related GTPases

  • Neuronal functional assays: Assessment in disease-relevant cell types

The most promising approach may utilize a phenotypic screen measuring ER morphology in ATL1-mutant cells, followed by mechanistic deconvolution to identify direct vs. indirect modulators of ATL1 function.

What are the key considerations for translating ATL1 research findings from cellular models to clinical applications?

Translating ATL1 research findings to clinical applications requires addressing several critical considerations:

• Model relevance assessment:

  • Human vs. model organism differences: Validation in human neurons

  • Cell type specificity: Focus on affected neuronal populations

  • Developmental timing: Accounting for age-dependent effects

  • Disease variant representation: Testing across multiple mutations

• Therapeutic development pathway:

  • Target validation: Confirmation that modulating ATL1 ameliorates disease-relevant phenotypes

  • Biomarker identification: Development of outcome measures for clinical trials

  • Therapeutic modality selection: Gene therapy, small molecule, protein replacement

  • Delivery challenges: Blood-brain barrier penetration, neuronal targeting

• Clinical trial design considerations:

  • Patient stratification: By mutation type, disease stage, or biomarker status

  • Outcome measures: Sensitive to disease progression and meaningful to patients

  • Trial duration: Appropriate for detecting changes in slowly progressive disease

  • Novel trial designs: Adaptive, basket, or platform trials for rare diseases

• Ethical and practical issues:

  • Early diagnosis: Development of genetic counseling frameworks

  • Natural history studies: Understanding disease progression

  • Patient engagement: Inclusion of patient perspectives in outcome measure selection

  • Resource allocation: Addressing challenges of developing therapies for ultra-rare disorders

Successful translation requires multidisciplinary collaboration between basic scientists, clinicians, industry partners, and patient advocacy groups to overcome the significant challenges inherent in developing treatments for rare neurological disorders like ATL1-related HSP.

What are the optimal methods for visualizing and quantifying ATL1-mediated membrane fusion events?

Visualizing and quantifying ATL1-mediated membrane fusion requires specialized techniques:

• In vitro reconstitution systems:

  • Fluorescence dequenching assays: Measuring lipid mixing via fluorophore dilution

  • Content mixing assays: Using self-quenching fluorophores to detect aqueous compartment fusion

  • FRET-based approaches: Monitoring membrane proximity and fusion in real-time

  • Single-vesicle fusion assays: Directly observing individual fusion events via TIRF microscopy

• Cellular imaging approaches:

  • Split-fluorescent protein systems: Detecting ATL1 dimerization during fusion

  • Super-resolution microscopy: Resolving sub-diffraction limited fusion intermediates

  • Correlative light-electron microscopy: Connecting molecular events to ultrastructure

  • Live-cell imaging with photo-activatable markers: Tracking ER dynamics

• Quantification metrics:

  • Fusion efficiency: Percentage of successful fusion events

  • Fusion kinetics: Rate constants for different steps in the fusion process

  • Energy requirements: GTP consumption per fusion event

  • Oligomerization state: Number of ATL1 molecules required per fusion event

• Analysis software and tools:

  • Custom MATLAB/Python analysis pipelines: Automated tracking of fusion events

  • Machine learning approaches: Classification of fusion intermediates

  • Reaction kinetics modeling: Fitting experimental data to mechanistic models

These methods allow researchers to dissect the specific steps in membrane fusion that are affected by disease-causing mutations, potentially identifying intervention points for therapeutic development.

How can multi-omics approaches be integrated to understand the systemic effects of ATL1 dysfunction?

Integrating multi-omics approaches provides a comprehensive view of ATL1 dysfunction:

• Multi-omics data acquisition:

  • Transcriptomics: RNA-seq to identify dysregulated gene expression

  • Proteomics: Mass spectrometry to assess protein abundance changes

  • Metabolomics: Profiling of metabolite alterations

  • Lipidomics: Characterization of membrane lipid composition changes

  • Interactomics: Proximity labeling to map protein-protein interactions

• Integration strategies:

  • Network analysis: Construction of integrated molecular networks

  • Pathway enrichment: Identification of affected biological processes

  • Causal reasoning: Inferring upstream drivers of observed changes

  • Multi-layer network modeling: Connecting different omics layers

• Cell type-specific approaches:

  • Single-cell multi-omics: Capturing heterogeneity in neuronal responses

  • Spatial transcriptomics/proteomics: Mapping changes along axonal processes

  • Compartment-specific analysis: Distinguishing cell body vs. axonal effects

• Temporal dynamics:

  • Time-course experiments: Capturing disease progression

  • Acute vs. chronic effects: Distinguishing primary from compensatory changes

  • Development stages: Identifying critical windows for intervention

Integration of these approaches can reveal unexpected connections, such as the recently discovered link between ATL1 dysfunction and lysosomal proteolytic capacity , potentially identifying novel therapeutic targets beyond direct modulation of ATL1 itself.

What computational modeling approaches are most useful for predicting the effects of ATL1 mutations on protein structure and function?

Computational modeling offers valuable insights into ATL1 mutation effects:

• Structural modeling techniques:

  • Homology modeling: Building models based on related protein structures

  • Molecular dynamics simulations: Predicting dynamic behavior and conformational changes

  • Protein-protein docking: Modeling ATL1 oligomerization and interactions

  • Free energy calculations: Estimating stability changes due to mutations

• Specialized ATL1 modeling considerations:

  • Membrane environment integration: Incorporating lipid bilayer effects

  • GTP binding/hydrolysis modeling: Simulating the catalytic cycle

  • Conformational transitions: Capturing large-scale structural changes during fusion

  • Oligomerization interfaces: Predicting effects on protein complex formation

• Machine learning approaches:

  • Variant effect prediction: Classifying mutations as pathogenic or benign

  • Structure-based deep learning: Directly predicting functional consequences

  • Feature extraction: Identifying critical residues for specific functions

  • Transfer learning: Leveraging information from related GTPases

• Validation and refinement strategies:

  • Integration with experimental data: Refining models based on biochemical results

  • Iterative prediction-validation cycles: Improving accuracy through testing

  • Ensemble approaches: Combining multiple modeling techniques

  • Uncertainty quantification: Assessing confidence in predictions

These computational approaches can predict the specific molecular mechanisms by which mutations like the recently identified N417ins insertion affect protein function , guiding experimental design and potentially informing personalized therapeutic strategies.

What are the most authoritative databases and repositories for ATL1 structure, function, and disease-related information?

Key resources for ATL1 research include:

• Protein structure and function databases:

  • UniProt: Comprehensive protein annotation including ATL1 function, subcellular localization, and disease associations

  • Protein Data Bank (PDB): Repository of experimentally determined ATL1 structures

  • AlphaFold DB: AI-predicted structures of ATL1 and its interaction partners

  • STRING: Protein-protein interaction network information

• Genetic and disease resources:

  • OMIM: Detailed information on ATL1-related disorders (SPG3A, HSN1D)

  • ClinVar: Clinical interpretations of ATL1 variants

  • gnomAD: Population frequency data for ATL1 variants

  • DECIPHER: Database of genomic variants and phenotypes

• Neurodegeneration-specific resources:

  • Neuromuscular Disease Center: Clinical information on HSP subtypes

  • HSP databases: Specialized repositories of HSP-causing mutations

  • SPG3A/ATL1 mutation databases: Collections of known pathogenic variants

• Experimental resources:

  • Addgene: Repository of ATL1 expression constructs

  • Cell line repositories: Sources of patient-derived cells

  • Allen Brain Atlas: Expression patterns in the nervous system

  • Human Protein Atlas: Tissue-specific expression and localization data

These resources collectively provide a foundation for ATL1 research, enabling investigators to access current knowledge, avoid duplication of efforts, and build upon existing findings.

What are the recommended guidelines for reporting ATL1 mutation nomenclature in research publications?

Standardized reporting of ATL1 mutations is essential for clear communication:

• Sequence reference standards:

  • Gene reference: Use HGNC-approved gene symbol (ATL1)

  • Transcript reference: Specify NCBI RefSeq transcript (e.g., NM_015915.4)

  • Protein reference: Use UniProt accession number (Q8WXF7)

• Mutation nomenclature conventions:

  • Follow HGVS guidelines: Human Genome Variation Society standards

  • DNA level notation: c.1250_1251insAAC (for the N417ins mutation)

  • Protein level notation: p.Asn417_Tyr418insAsn or p.N417_Y418insN

  • Include both DNA and protein level descriptions

• Clinical information reporting:

  • Phenotype description: Use standardized terminology (e.g., SPG3A)

  • Age of onset: Specify early-onset vs. adult-onset

  • Pure vs. complex: Indicate presence of additional neurological features

  • Family history: Document inheritance pattern (dominant, recessive, de novo)

• Functional classification:

  • Effect on protein: Loss-of-function, gain-of-function, dominant negative

  • Molecular consequence: GTPase activity, dimerization, membrane binding

  • Cellular impact: ER morphology, membrane fusion, lysosomal function