ASRGL1 Antibody

What is ASRGL1 and what are its primary enzymatic functions in cellular metabolism?

ASRGL1 (Asparaginase Like 1, also known as ALP or CRASH) is a member of the Ntn-hydrolase family that possesses dual enzymatic functions: L-asparaginase and beta-aspartyl peptidase activity. This protein plays a crucial role in cellular metabolism through:

• Catalyzing the hydrolysis of L-asparagine (Asn) to L-aspartic acid (Asp) and ammonia

• Processing beta-aspartyl dipeptides and their methyl esters, including beta-L-Asp-L-Phe, beta-L-Asp-L-Phe methyl ester (aspartame), beta-L-Asp-L-Ala, beta-L-Asp-L-Leu, and beta-L-Asp-L-Lys

• Potentially contributing to the production of L-aspartate, which functions as an excitatory neurotransmitter in certain brain regions

Methodologically important: When studying ASRGL1 function, researchers should note that it does not possess aspartylglucosaminidase activity and shows no activity toward GlcNAc-L-Asn or glutamine . These specificity characteristics are critical when designing experiments to assess enzymatic activity.

What applications are ASRGL1 antibodies commonly used for in biomedical research?

ASRGL1 antibodies have been validated for multiple applications, with varying degrees of optimization depending on the specific antibody clone and manufacturer:

Methodological approach: When implementing a new ASRGL1 antibody in your research, validation using positive controls (e.g., HeLa cells) is essential, as observed molecular weights can vary (32-40 kDa, 20-25 kDa, 15-19 kDa) depending on the detection system and sample preparation methods .

What are the appropriate storage conditions for maintaining ASRGL1 antibody activity?

Most commercially available ASRGL1 antibodies require specific storage conditions to maintain functionality:

• Optimal storage temperature: -20°C for long-term storage

• Buffer composition: Typically supplied in PBS with 0.02-0.1% sodium azide and 50% glycerol at pH 7.3

• Stability: Unopened kits can generally be stored at 2-8°C for 1 year

• Once opened: Products should be used within 1 month

• Aliquoting: For some preparations, aliquoting is unnecessary for -20°C storage

Methodological note: When handling ASRGL1 antibodies for sensitive applications like IHC or IF, minimize freeze-thaw cycles and consider preparing working dilutions fresh on the day of experiment to maintain consistent staining intensity.

How is ASRGL1 expression altered in ALS pathology, and what methodological approaches are needed for its study?

Recent research has revealed a critical relationship between ASRGL1 and amyotrophic lateral sclerosis (ALS):

• ASRGL1 expression is significantly reduced in brain samples from ALS patients compared to non-neurological controls (ANOVA; p = 0.0004)

• Strong negative correlation exists between ASRGL1+ cells and the presence of cytoplasmic TDP-43 (Pearson r = −0.84; p value = 0.008)

• Both protein levels (Western blotting) and mRNA levels (qPCR) of ASRGL1 are lower in ALS brain samples

• Sex-specific differences: Statistical significance was maintained for males but not for females in some analyses

Methodological considerations for ALS research:

• Automated staining systems are recommended to avoid differences due to manual staining variability

• Comparison between affected areas (pre-motor cortex) and unaffected areas (visual cortex) within the same individuals provides valuable control data

• Multiple ASRGL1 antibodies should be used for validation (e.g., Atlas HPA029725 and Atlas HPA055572)

• Co-localization studies with ASRGL1 and TDP-43 by immunofluorescence are important for understanding their relationship in disease

What is the relationship between ASRGL1 and immune cell infiltration in hepatocellular carcinoma?

ASRGL1 has emerging significance in hepatocellular carcinoma (HCC) research:

Methodological approach for HCC studies:

What are the optimal immunohistochemical protocols for ASRGL1 detection in different tissue types?

Successful ASRGL1 immunodetection requires optimization of several parameters:

• Antigen retrieval: TE buffer pH 9.0 is generally recommended; alternatively, citrate buffer pH 6.0 can be used depending on tissue type

• Antibody dilutions for IHC: 1:50-1:500 range, with specific optimization needed for each tissue type

• Positive control tissues: HeLa cells for IF/ICC, human gliomas for IHC

• Automated vs. manual staining: Automated systems are preferred, especially for comparative studies, to minimize technical variability

• Detection systems: Standard DAB visualization works well, but fluorescent detection enables co-localization studies with other proteins

Tissue-specific considerations:

• Brain tissue: Requires careful blocking of endogenous peroxidase and potentially lower antibody concentrations

• Tumor samples: May show heterogeneous expression requiring quantification across multiple fields

• Formalin-fixed paraffin-embedded (FFPE) vs. frozen sections: Both have been successfully used, with different optimal protocols

How can researchers verify ASRGL1 antibody specificity and troubleshoot inconsistent results?

Verification of ASRGL1 antibody specificity is crucial for reliable research outcomes:

• Multiple antibody validation:

  • Compare results from different antibody clones targeting different epitopes

  • Use both polyclonal and monoclonal antibodies as complementary approaches

  • Verify with antibodies from different host species (rabbit, mouse, goat)

• Expected molecular weights:

  • Primary band: 32-40 kDa (full-length protein)

  • Additional bands: 20-25 kDa and 15-19 kDa (potentially processed forms)

  • Both reported variants (NP_001077395.1 and NP_079356.3) represent identical protein

• Troubleshooting inconsistent results:

  • Verify antibody immunogen sequence matches your species of interest

  • For the internal region antibody (ABIN238597), the immunogen peptide is EKHEKGAQKTDCQ

  • Consider using antibodies purified via antigen affinity chromatography for higher specificity

  • Test blocking peptides to confirm specificity of signal

• Positive controls:

  • HeLa cells have been validated for WB, IP, and IF applications

  • Human brain tissue serves as a good positive control for IHC applications

What emerging research links ASRGL1 dysfunction to neurodegenerative disease mechanisms?

Recent studies have revealed important connections between ASRGL1 and neurodegenerative processes:

• ASRGL1 deficiency has been identified as a potential trigger for TDP-43 proteinopathy in ALS

• Co-localization studies show that in control brains, ASRGL1 co-localizes with predominantly nuclear TDP-43

• In ALS brain samples with low ASRGL1 levels, TDP-43 is found almost exclusively in the cytoplasm

• Quantitative analysis shows dramatically reduced numbers of neurons and astrocytes positive for ASRGL1 in ALS brains compared to controls

Methodological considerations for neurodegenerative research:

• Brain region specificity: Compare affected areas (e.g., pre-motor cortex/BA6) with unaffected areas (e.g., visual cortex/BA17)

• Sex-specific analysis: Male vs. female differences have been observed in ASRGL1 expression patterns in ALS

• Cellular localization: Both immunohistochemistry and immunofluorescence approaches are valuable for determining ASRGL1 cellular distribution

• Contiguous section analysis: Staining adjacent sections for ASRGL1 and TDP-43 enables correlation studies within the same anatomical regions

What are the critical parameters for optimizing ASRGL1 antibody-based ELISA assays?

ASRGL1 ELISA development requires attention to several key parameters:

• Assay principle: Sandwich enzyme immunoassay technique is most common

• Sample types validated: Human serum, plasma, cell culture supernatants, tissue homogenates, and other biological fluids

• Antibody orientation: Pre-coating with capture antibody specific for Human ASRGL1, followed by detection antibody

• Optimization considerations:

  • Antibody pair selection (capture and detection)

  • Blocking buffer composition

  • Sample dilution factors

  • Incubation times and temperatures

  • Wash steps optimization

  • Substrate development time

Standard preparation and handling:

• Lyophilized standards typically should not be reused after reconstitution

• Standard/sample diluent (R1), biotin-conjugate antibody diluent (R2), and streptavidin-HRP diluent (R3) have specific formulations that affect assay performance

• Storage of reconstituted reagents at 2-8°C for up to 1 month is generally possible

How should researchers address potential cross-reactivity when using ASRGL1 antibodies in multi-species studies?

Cross-reactivity considerations are essential when designing experiments across multiple species:

Methodological approaches for cross-reactivity assessment:

• Sequence alignment analysis: Compare the immunogen sequence across species of interest

• Validation in multiple species: Test antibody in known positive and negative control tissues from each species

• Blocking peptide controls: Use immunizing peptide to confirm specificity of signal

• Knockout/knockdown validation: When available, use ASRGL1-deficient samples as negative controls

What are the considerations for selecting between different ASRGL1 antibody formats for multiplexed immunofluorescence studies?

Multiplexed immunofluorescence studies require careful antibody selection:

• Host species considerations:

  • Choose primary antibodies raised in different host species to avoid cross-reactivity

  • Common ASRGL1 antibody hosts include rabbit, mouse, and goat

  • For triple or quadruple staining, plan antibody combinations carefully based on available secondary antibodies

• Epitope targeting:

  • Different region-specific antibodies are available:

    • Internal region antibodies

    • C-terminal antibodies

    • Full-length protein antibodies

    • Specific amino acid region antibodies (e.g., AA 1-308, AA 1-180, AA 251-300)

  • Select antibodies targeting different regions when co-localizing ASRGL1 with interaction partners

• Signal amplification options:

  • Direct conjugates vs. secondary detection

  • Tyramide signal amplification for weak signals

  • Consider biotin-streptavidin systems for enhanced sensitivity

• Co-localization with TDP-43:

  • Published protocols have successfully demonstrated co-localization of ASRGL1 and TDP-43

  • This approach is particularly valuable for ALS research

  • Both proteins can be visualized simultaneously using appropriate fluorophore combinations

How does ASRGL1 expression correlate with tumor progression, and what methodological approaches enable robust biomarker development?

ASRGL1 shows promising potential as a biomarker for various cancers:

• Hepatocellular carcinoma (HCC):

  • Upregulated in HCC compared to adjacent tissues

  • High expression correlates with poor clinical outcomes

  • LinkedOmics, UALCAN, and GEPIA databases provide valuable resources for expression analysis

  • c-Bioportal can be used to explore mutations in ASRGL1 in HCC

• Endometrial tumors:

  • Low ASRGL1 expression associated with poor outcomes

  • Serves as a biomarker for prognostic assessment

• Breast cancer:

  • Strong expression promotes proliferation and inhibits apoptosis

Methodological approaches for biomarker development:

• Multi-database analysis: HCCDB, Oncomine, TIMER 2.0 provide complementary insights

• Multi-technique validation: Combine Western blotting, IHC, and qPCR for robust verification

• Correlation with clinical outcomes: Use Kaplan-Meier survival analysis to establish prognostic value

• Immune correlation analysis: TIMER 2.0 and GEPIA databases enable assessment of relationship with immune infiltration

What are the emerging trends in ASRGL1 research and potential therapeutic applications?

ASRGL1 research is expanding into several promising areas:

• Neurodegenerative disease applications:

  • Loss of ASRGL1 and its relationship to TDP-43 proteinopathy in ALS represents a novel therapeutic target

  • The negative correlation between ASRGL1+ cells and cytoplasmic TDP-43 suggests potential for intervention strategies

• Cancer therapy approaches:

  • ASRGL1 has been used successfully to treat hematological malignancies

  • ASRGL1's role in asparagine metabolism suggests potential application in asparagine-dependent solid tumors

  • The correlation with immune infiltration in HCC points to possible immunomodulatory approaches

• Biomarker development:

  • Prognostic value in multiple cancer types

  • Potential for early disease detection

  • Companion diagnostic for treatment selection

• Technical innovations:

  • Development of more specific antibodies targeting functional domains

  • Application in advanced imaging techniques

  • Integration with multi-omics datasets for systems biology approaches

Methodological considerations for emerging research:

• Interdisciplinary approaches combining proteomics, genomics, and functional studies

• Development of patient-derived models for personalized medicine applications

• Therapeutic antibody development targeting ASRGL1 modulation

How should researchers interpret ASRGL1 antibody signals across different subcellular compartments?

Subcellular localization of ASRGL1 provides important functional insights:

• Normal cellular distribution:

  • In control brain tissues, ASRGL1 co-localizes with nuclear TDP-43

  • Expression in both neurons and astrocytes has been reported

  • Cytoplasmic distribution follows patterns consistent with enzymatic function

• Pathological changes:

  • In ALS brain samples, drastically reduced ASRGL1 levels correlate with TDP-43 mislocalization

  • Even in low-expression states, remaining ASRGL1 may co-localize with cytoplasmic TDP-43

  • Changes in subcellular distribution may precede clinical manifestations

• Interpretation challenges:

  • Distinguish between specific signal and background

  • Consider fixation artifacts that may alter apparent localization

  • Process controls (no primary antibody, isotype controls) are essential

  • Confocal microscopy may provide better resolution of subcellular compartments than widefield microscopy

Methodological validation approaches:

• Co-staining with compartment-specific markers (nuclear, cytoplasmic, membrane)

• Subcellular fractionation followed by Western blotting

• Comparison of different fixation and permeabilization protocols

What controls and validation steps are essential when implementing ASRGL1 antibodies in new experimental systems?

Rigorous validation is critical when introducing ASRGL1 antibodies to new experimental systems:

• Essential controls:

  • Positive control: HeLa cells have been validated for many ASRGL1 antibodies

  • Negative controls: Isotype-matched irrelevant antibodies

  • Blocking experiments: Pre-incubation with immunizing peptide should abolish specific signal

  • Concentration gradients: Titration to determine optimal antibody concentration

• Validation across multiple techniques:

  • Correlation between protein (Western blot) and mRNA (qPCR) expression

  • Complementary techniques (e.g., immunofluorescence and immunohistochemistry)

  • Orthogonal approaches (mass spectrometry, RNA-seq)

• Species-specific validation:

  • When using antibodies in non-human models, validate specificity

  • Test multiple antibodies targeting different epitopes

  • Consider sequence homology between species when interpreting results

• Functional validation:

  • Knockdown/knockout studies with corresponding loss of signal

  • Overexpression studies with increased signal intensity

  • Correlation with enzymatic activity measurements

How should researchers address discrepancies in ASRGL1 molecular weight detection in Western blotting?

ASRGL1 antibodies may detect various molecular weight forms, requiring careful interpretation:

• Expected molecular weight patterns:

  • Primary band: 32-40 kDa (full-length protein)

  • Secondary bands: 20-25 kDa and 15-19 kDa (likely processed forms)

  • Calculated molecular weight: 308 aa, 32 kDa

  • Both reported variants (NP_001077395.1 and NP_079356.3) represent identical protein

• Sources of variability:

  • Post-translational modifications

  • Proteolytic processing

  • Sample preparation differences

  • Reducing vs. non-reducing conditions

  • Gel percentage and running conditions

  • Exposure time variations

• Troubleshooting approaches:

  • Compare multiple antibodies targeting different epitopes

  • Include positive control lysates (e.g., HeLa cells)

  • Optimize protein extraction methods

  • Test different sample preparation buffers

  • Consider gradient gels for better resolution of multiple bands

• Verification strategies:

  • Immunoprecipitation followed by mass spectrometry

  • Expression of tagged recombinant ASRGL1

  • Peptide competition assays

  • ASRGL1 knockout/knockdown controls

What are the key considerations for quantitative analysis of ASRGL1 expression in patient samples?

Quantitative assessment of ASRGL1 requires standardized approaches:

• Immunohistochemistry quantification:

  • Digital image analysis for consistent scoring

  • Consideration of both staining intensity and percentage of positive cells

  • Automated staining systems to minimize batch effects

  • Blinded assessment by multiple observers

  • Appropriate statistical methods for analysis (e.g., ANOVA, correlation coefficients)

• Western blot quantification:

  • Loading controls appropriate for tissue type (β-actin, GAPDH)

  • Normalization to total protein using stain-free technology

  • Linear dynamic range verification

  • Technical and biological replicates

  • Statistical analysis accounting for variability

• ELISA-based quantification:

  • Standard curve optimization

  • Sample dilution optimization

  • Spike-recovery experiments

  • Inter- and intra-assay coefficient of variation assessment

  • Limit of detection and quantification determination

• qPCR for mRNA quantification:

  • Reference gene selection appropriate for tissue type

  • Primer efficiency verification

  • Multiple technical replicates

  • Delta-Delta Ct or standard curve methods

  • Correlation with protein expression

How can researchers integrate ASRGL1 data with broader -omics datasets for systems biology approaches?

Integration of ASRGL1 research into systems biology requires sophisticated approaches:

• Multi-omics integration strategies:

  • Correlation of ASRGL1 protein levels with transcriptomics data

  • Network analysis to identify interaction partners

  • Pathway enrichment to understand functional context

  • LinkedOmics can analyze genes co-expressed with ASRGL1 and regulators including kinases, miRNAs, and transcription factors

• Functional annotation approaches:

  • Gene Ontology (GO) terms analysis

  • Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway mapping

  • Gene Set Enrichment Analysis (GSEA)

  • Protein-protein interaction networks

• Disease-specific databases and resources:

  • TIMER 2.0 and GEPIA for immune infiltration correlation

  • UALCAN and Kaplan-Meier plotter for survival analysis

  • c-Bioportal for mutation analysis

  • HCCDB for hepatocellular carcinoma-specific data

• Methodological considerations:

  • Normalization and batch correction across datasets

  • Statistical methods appropriate for high-dimensional data

  • Validation of computational predictions with experimental approaches

  • Integration of clinical metadata for translational relevance