ASMTL Antibody

What is ASMTL and what applications are commonly used for its detection?

ASMTL (acetylserotonin O-methyltransferase-like) is a protein with a bifunctional nature - its N-terminus is similar to the multicopy associated filamentation (maf) protein of Bacillus subtilis, while its C-terminus shares similarity with N-acetylserotonin O-methyltransferase . ASMTL is encoded by a gene located in the pseudoautosomal region 1 (PAR1) of X and Y chromosomes, with three transcript variants encoding different isoforms identified .

Common applications for ASMTL detection include:

It's recommended that researchers titrate these antibodies in each testing system to obtain optimal results, as performance can be sample-dependent .

What is the expected molecular weight for ASMTL in experimental studies?

When working with ASMTL antibodies, researchers should expect to observe:

• Calculated molecular weight: 69 kDa

• Observed molecular weight in experimental conditions: 69-75 kDa

This slight variation in observed molecular weight may be due to post-translational modifications or splice variants. When performing Western blot validation, researchers have successfully detected ASMTL in various human cell lines including A549 cells, HeLa cells, HL-60 cells, and L02 cells, as well as in human testis tissue .

What are the key specifications researchers should consider when selecting an ASMTL antibody?

When selecting an ASMTL antibody for research, consider these critical specifications:

For optimal results, store the antibody at -20°C. Most formulations remain stable for one year after shipment, with aliquoting generally unnecessary for -20°C storage .

How should researchers optimize experimental conditions for ASMTL antibody applications?

For Western blotting:

• Start with dilutions between 1:500-1:2000

• For antigen retrieval in IHC, use TE buffer pH 9.0 (recommended) or alternatively citrate buffer pH 6.0

• Positive controls should include human testis tissue, A549 cells, HeLa cells, HL-60 cells, or L02 cells

• If experiencing non-specific binding, increase blocking time or adjust antibody concentration

For immunohistochemistry:

• Begin with 1:50-1:200 dilution

• Positive tissues: human prostate cancer tissue and rectum (showing strong cytoplasmic positivity in glandular cells)

• Use recommended antigen retrieval methods specific to the antibody

For immunofluorescence:

• Start with 1:20-1:200 dilution or 0.25-2 μg/mL

• A549 cells and U-2 OS cells show positive detection

• Expect cytosolic localization pattern

What methodological approaches can researchers use to validate ASMTL antibody specificity?

Antibody validation is crucial given recent concerns about reproducibility in antibody-based research. Several complementary approaches should be used:

• Western blot validation:

  • Compare observed molecular weight (69-75 kDa) with calculated weight (69 kDa)

  • Test both positive control samples (A549, HeLa cells) and negative controls

  • Include loading controls (β-actin or GAPDH)

• Knockdown/knockout validation:

  • Compare antibody signal in wild-type vs. ASMTL-knockdown cells

  • This addresses concerns highlighted in studies about antibody validity, similar to cases where inadequately validated antibodies led research in incorrect directions

• Subcellular fractionation:

  • Verify cytosolic localization pattern observed in U-2 OS cells

  • Use the PARIS™ Kit (Ambion) to isolate nuclear and cytoplasmic fractions

  • Monitor isolated RNAs by Western blot method

• Multiple antibody verification:

  • Test antibodies targeting different epitopes of ASMTL (N-terminal vs. C-terminal regions)

  • Compare reactivity patterns across different antibodies

• Mass spectrometry validation:

  • Consider immunoprecipitation followed by mass spectrometry to confirm target identity

  • This provides orthogonal validation beyond immunoassays

What is the relationship between ASMTL-AS1 and cancer progression, and how can researchers investigate this connection?

ASMTL-AS1 is a long non-coding RNA related to ASMTL that exhibits significant tumor suppressor properties. Research has shown:

How can active learning approaches improve ASMTL antibody-antigen binding prediction?

Active learning represents a promising approach to enhance experimental efficiency in antibody-antigen binding prediction:

• Basic methodology:

  • Start with a small labeled subset of data

  • Iteratively expand the labeled dataset based on strategic selection

  • Develop machine learning models to predict target binding

• Key advantages for ASMTL antibody research:

  • Reduces experimental costs by strategically selecting which experiments to perform

  • Particularly valuable for predicting out-of-distribution interactions (where test antibodies/antigens aren't represented in training data)

  • Can analyze many-to-many relationships between antibodies and antigens

• Performance improvements:

  • Reduces the number of required antigen mutant variants by up to 35%

  • Speeds up the learning process by 28 steps compared to random baseline

  • Three specific algorithms significantly outperformed random data labeling

• Implementation methodology:

  • Use the Absolut! simulation framework for evaluating active learning strategies

  • Develop library-on-library approaches where many antigens are probed against many antibodies

  • Apply machine learning models to analyze the resulting data

This approach represents a significant advancement for researchers working with ASMTL antibodies, potentially reducing experimental costs while improving prediction accuracy.

What protocols should researchers follow for RNA immunoprecipitation assays when studying ASMTL-related non-coding RNAs?

When investigating the interaction between ASMTL-AS1 and potential binding partners like miR-1228-3p, RNA immunoprecipitation (RIP) assays provide valuable insights:

• Recommended protocol:

  • Use the EZ-Magna RIP RNA Binding Protein Immunoprecipitation Kit (Millipore)

  • Include antibodies against Ago2 (key component of the RNA-induced silencing complex)

  • Use normal IgG as a negative control

• Procedural steps:

  • Process cells with IP lysis buffer to acquire cell lysates

  • Mix with specific antibodies at constant speed at 4°C

  • Culture the mixture with beads for 2 hours

  • Rinse in IP lysis buffer and elute for Western blot analysis

  • Measure precipitated RNAs via qRT-PCR

• Complementary approaches:

  • RNA pull-down assay using biotin-labeled DNA probe complementary to ASMTL-AS1

  • Luciferase reporter assay with wild-type and mutated binding sites

  • qRT-PCR to measure expression levels of potential target genes

• Data interpretation:

  • Compare enrichment of target RNAs in specific antibody precipitates versus IgG control

  • Validate findings using multiple approaches (RNA pull-down, luciferase reporter)

  • Confirm functional significance through gain/loss-of-function studies

By following these methodological approaches, researchers can reliably investigate the molecular mechanisms through which ASMTL-AS1 exerts its biological functions.

What considerations should researchers take into account when interpreting ASMTL antibody validation data?

Interpreting antibody validation data requires careful consideration of multiple factors:

• Validation across multiple applications:

  • An antibody that performs well in one application may not perform similarly in others

  • For ASMTL, validate across WB, IHC, IF/ICC based on expected application needs

  • Check validation data for specific applications (see validation images from manufacturers)

• Positive and negative controls:

  • Confirm detection in known positive samples (A549, HeLa cells)

  • Include appropriate negative controls (null cell lines, blocking peptides)

  • Be aware that cell/tissue-dependent expression patterns may affect results

• Detection method considerations:

  • For colorimetric detection, check for specific band staining at expected molecular weight

  • For chemiluminescence, verify signal intensity and specificity

  • With fluorescence, evaluate signal-to-noise ratio and localization pattern

• Potential issues to watch for:

  • Non-specific binding (additional unexpected bands)

  • Incorrect subcellular localization

  • Inconsistent results between different detection methods

  • Batch-to-batch variability in polyclonal antibodies

• Reproducibility considerations:

  • Compare findings with literature reports

  • Be aware of the potential for insufficiently validated antibodies leading research in incorrect directions, as highlighted in studies of other receptor antibodies

  • Consider orthogonal validation using independent techniques