MKLN1 Antibody

What is MKLN1 and what are its primary cellular functions?

MKLN1 (Muskelin 1) is an intracellular kelch repeat protein consisting of discoidin, LisH, CTLH, and kelch repeat structural domains with a molecular mass of approximately 130 kDa . Functionally, MKLN1:

• Acts as a component of the CTLH E3 ubiquitin-protein ligase complex that selectively accepts ubiquitin from UBE2H and mediates ubiquitination and subsequent proteasomal degradation of the transcription factor HBP1

• Facilitates internalization of the GABA receptor GABRA1 from the cell membrane via endosomes and subsequent GABRA1 degradation

• Mediates cell spreading and cytoskeletal responses to the extracellular matrix component THBS1

• Regulates cell adhesion and cytoskeletal dynamics

What types of MKLN1 antibodies are available for research applications?

Current research-grade MKLN1 antibodies fall into several categories:

How is MKLN1 antibody specificity validated in research settings?

Validation of MKLN1 antibodies typically involves multiple complementary approaches:

• Western blot analysis using cell lysates from multiple human cell lines (Jurkat, A431, Y79, 293T) to confirm recognition of the anticipated 85 kDa band

• Immunohistochemical staining of paraffin-embedded human tissue samples (such as prostate tissue) at standardized dilutions (e.g., 1/400)

• Cross-validation with molecular techniques (such as RNA interference) to confirm specificity of observed signals

• Verification through immunogen mapping (for example, antibodies targeting recombinant fragment proteins within Human MKLN1 aa 450-650)

What controls should be included when using MKLN1 antibodies in Western blot applications?

For rigorous experimental design with MKLN1 antibodies in Western blot:

• Positive controls: Include lysates from cell lines with known MKLN1 expression (Jurkat, A431, Y79, or 293T cells)

• Loading controls: Use housekeeping proteins (β-actin, GAPDH) to normalize protein loading

• Negative controls: Consider MKLN1-knockdown samples or non-expressing cell lines

• Antibody controls: Include secondary antibody-only controls to assess non-specific binding

• Molecular weight verification: Confirm band visualization at the expected 85 kDa (predicted size)

Standard Western blot protocol parameters for MKLN1:

• Primary antibody dilution: 1/1000 for recombinant monoclonal antibodies

• Secondary antibody (Goat anti-rabbit HRP): 1/2000 dilution

• Loading amount: 10 μg total protein per lane is typically sufficient

How should researchers design experiments to investigate MKLN1's role in cancer progression?

Based on recent findings implicating MKLN1 and its associated RNAs in multiple cancer types:

• Expression analysis strategy:

  • Compare MKLN1 protein levels between tumor tissues and adjacent normal tissues using immunohistochemistry and Western blot

  • Correlate expression with clinical parameters (tumor stage, differentiation, survival)

• Functional assessment approach:

  • Generate MKLN1 overexpression and knockdown cell models using appropriate cancer cell lines

  • Evaluate effects on:

    • Cell proliferation (Cell Counting Kit-8, Colony Formation, EdU assays)

    • Migration/invasion (Wound healing, Transwell assays)

    • Apoptosis (Flow cytometry)

• In vivo validation:

  • Develop xenograft mouse models using MKLN1-modulated cancer cells

  • Monitor tumor growth, metastasis, and survival outcomes

What methodological considerations are crucial when studying the relationship between MKLN1 protein and its associated RNAs?

When investigating the complex interplay between MKLN1 protein and its associated RNAs (MKLN1-AS lncRNA or circMKLN1):

• RNA stability assessment:

  • RNase R treatment to distinguish circular RNAs (resistant) from linear mRNAs (degraded)

  • Actinomycin D time course (0, 12, 24h) to compare decay rates between circular and linear forms

• Subcellular localization determination:

  • Nuclear/cytoplasmic fractionation followed by qRT-PCR to determine compartmentalization

  • Use appropriate controls (β-actin for cytoplasm, U6 for nucleus)

  • Fluorescence in situ hybridization (FISH) to visualize co-localization of MKLN1-derived RNAs with potential interacting partners

• Mechanism verification:

  • Luciferase reporter assays to validate direct RNA-RNA interactions

  • RNA immunoprecipitation (RIP) to confirm protein-RNA binding

  • Rescue experiments to establish functional relationships in regulatory networks

What are the optimal protocols for MKLN1 immunohistochemistry in different tissue types?

For paraffin-embedded human tissue samples:

• Antigen retrieval method:

  • High-pressure citrate buffer (pH 6.0) is recommended for MKLN1 antibodies in human prostate tissue

• Blocking parameters:

  • 10% normal goat serum is effective for reducing background

• Antibody dilutions and incubation:

  • Primary antibody: 1/400 dilution of polyclonal antibodies for optimal signal-to-noise ratio

  • Secondary detection system: HRP-conjugated anti-rabbit antibodies with optimization for tissue type

• Visualization technique:

  • ECL (enhanced chemiluminescence) for Western blot applications

  • DAB substrate for immunohistochemistry

How can researchers troubleshoot non-specific binding when using MKLN1 antibodies?

When encountering non-specific binding issues:

• Optimization strategies:

  • Titrate antibody concentration (typically starting from 1/1000 for WB, 1/400 for IHC)

  • Increase blocking agent concentration (5% to 10% serum or BSA)

  • Extend blocking time (1-2 hours at room temperature)

  • Include 0.1-0.3% Triton X-100 for better permeabilization in immunofluorescence

• Background reduction techniques:

  • Add 0.05-0.1% Tween-20 in wash buffers

  • Increase washing duration and frequency

  • Pre-absorb antibody with tissue/cell powder from non-target species

  • Consider using monoclonal antibodies for higher specificity in complex samples

• Validation approaches:

  • Perform peptide competition assays

  • Include MKLN1 knockdown samples as negative controls

  • Cross-validate with alternative antibody clones

How can MKLN1 antibodies be utilized to investigate the CTLH E3 ubiquitin-protein ligase complex function?

Given MKLN1's role in the CTLH E3 ubiquitin-protein ligase complex:

• Co-immunoprecipitation strategy:

  • Use anti-MKLN1 antibodies for pulldown experiments to identify interaction partners

  • Analyze complex formation through subsequent Western blotting for known complex members

  • Validate protein-protein interactions with reciprocal IP experiments

• Ubiquitination assay approach:

  • Combine MKLN1 antibodies with anti-ubiquitin detection to monitor substrate modification

  • Track HBP1 transcription factor degradation following MKLN1 manipulation

  • Employ proteasome inhibitors to accumulate ubiquitinated substrates

• Functional analysis:

  • Investigate the selective ubiquitin acceptance from UBE2H

  • Monitor proteasomal degradation pathways of HBP1 following complex formation

  • Analyze downstream effects on transcriptional regulation

What are the methodological approaches for investigating MKLN1-AS as a competing endogenous RNA in cancer progression?

Based on findings that MKLN1-AS functions as a ceRNA:

• Expression correlation analysis:

  • Quantify MKLN1-AS, target miRNAs (miR-654-3p, miR-185-5p), and downstream targets (HDGF, TEAD1) using qRT-PCR

  • Establish statistical correlations between expression patterns in clinical samples

• Mechanistic verification protocol:

  • RNA pulldown assays to confirm direct binding between MKLN1-AS and target miRNAs

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

  • Rescue experiments to validate the regulatory axis (e.g., MKLN1-AS/miR-654-3p/HDGF)

• Functional characterization:

  • Evaluate effects of MKLN1-AS modulation on cancer hallmarks

  • Combine with miRNA inhibitors/mimics to confirm pathway specificity

  • Validate findings in patient-derived xenograft models

How can researchers differentiate between the functions of MKLN1 protein and its associated RNAs (MKLN1-AS lncRNA and circMKLN1)?

To distinguish between the potentially divergent roles:

• Selective modulation strategy:

  • Design targeted siRNAs/shRNAs specific to MKLN1 mRNA but not affecting MKLN1-AS or circMKLN1

  • Use antisense oligonucleotides targeting the unique back-splice junction of circMKLN1

  • Develop CRISPR-based approaches for selective genomic disruption

• Differential expression analysis:

  • Quantify all three molecules (MKLN1 protein, MKLN1-AS, circMKLN1) across tissue samples

  • Identify contexts where their expression patterns diverge

  • Correlate with different clinical parameters to distinguish functional associations

• Subcellular localization comparison:

  • Conduct immunofluorescence for MKLN1 protein

  • Perform RNA FISH for MKLN1-AS and circMKLN1

  • Analyze co-localization patterns to infer potential functional interactions

What is the potential significance of MKLN1 and its associated RNAs in disease biomarker development?

The biomarker potential of MKLN1-related molecules can be evaluated through:

How can contradictory findings regarding circMKLN1's role in different cancer types be reconciled methodologically?

To address the apparent contradiction that circMKLN1 acts as a tumor suppressor in retinoblastoma but may promote cancer in other contexts:

• Context-dependent mechanism analysis:

  • Systematically compare miRNA binding partners across cancer types

  • In retinoblastoma: circMKLN1 sponges miR-425-5p, promoting PDCD4 expression and inhibiting tumor growth

  • In other contexts: circMKLN1 may bind different miRNAs, leading to distinct downstream effects

• Cell-type specific investigation:

  • Conduct parallel experiments in multiple cell lines representing different tissue origins

  • Analyze tissue-specific transcription factors that may influence circMKLN1 function

  • Evaluate epigenetic modifications that might alter RNA-RNA interactions

• Technical standardization:

  • Employ consistent methodology across studies (identical circRNA detection techniques)

  • Standardize quantification approaches and normalization methods

  • Validate findings with multiple orthogonal techniques