AHA1 Antibody

What is AHA1 and why is it an important target for antibody-based research?

AHA1 (Activator of Hsp90 ATPase 1) is a co-chaperone protein that stimulates the ATPase activity of the molecular chaperone Hsp90, accelerating the conformational cycle during which client proteins attain their final shape . Recent research has revealed that AHA1 also functions as an autonomous chaperone, preventing aggregation of stress-denatured proteins and facilitating their ubiquitination by the E3 ubiquitin ligase CHIP . AHA1 has gained significant research interest due to its dual functionality and involvement in cancer progression, particularly in colorectal cancer where its expression correlates with tumor stage and metastasis .

The protein has emerged as a valuable research target because it appears to regulate cancer cell migration and invasion through EMT signaling pathways via Snail, E-cadherin, pSRC, and pAKT . Additionally, AHA1's independent chaperone function suggests a role in cellular protein quality control mechanisms beyond its Hsp90-related activities . Thus, antibodies against AHA1 are essential tools for investigating these diverse biological functions and their implications in disease processes.

What applications can AHA1 antibodies be optimally used for in research?

AHA1 antibodies have demonstrated utility across multiple experimental applications:

For western blotting applications, AHA1 antibodies have successfully detected differential expression across various colon cancer cell lines, from early-stage (HT-29) to highly metastatic lines (HCT-116) . In immunohistochemistry, they have effectively distinguished AHA1 expression between colorectal cancer tissues (average score = 2.15) and adjacent normal tissues (average score = 1.35) .

Different applications may require specific antibody clones or formats. Always validate the antibody for your specific application and experimental system to ensure reliable results.

How can I validate the specificity of an AHA1 antibody for my research?

Thorough validation of AHA1 antibodies is essential for generating reliable research data. Consider implementing the following comprehensive validation strategy:

Positive controls:

• Use cell lines with known high AHA1 expression (HCT116, KM12SA, or Lovo colorectal cancer cells)

• Include recombinant AHA1 protein as a reference standard

• Utilize tissues with documented AHA1 overexpression (colorectal cancer tissue samples)

Negative controls:

• Generate AHA1 knockdown cell lines using siRNA or CRISPR/Cas9

• Use cell types with naturally low AHA1 expression (normal colon fibroblast cells like CCD18Co)

• Include antibody-only controls (omitting primary antibody)

Specificity verification:

• Perform peptide competition assays using the immunizing peptide

• Test for cross-reactivity with the related protein AHSA2

• Verify size-appropriate band detection (AHA1: ~38 kDa)

• Confirm subcellular localization patterns match known distribution

Cross-validation approaches:

• Compare results using multiple antibodies targeting different AHA1 epitopes

• Correlate protein detection with mRNA expression data

• Verify knockdown or overexpression effects using both RNA and protein detection

Remember that AHA1 belongs to a family that includes AHSA2 (a pseudogene), requiring careful evaluation of antibody cross-reactivity with related proteins .

What expression patterns of AHA1 should I expect in different cell and tissue types?

Based on published research, AHA1 exhibits distinctive expression patterns across various cell types and tissues:

AHA1 expression demonstrates a clear correlation with cancer progression, particularly in colorectal cancer. Higher expression levels are significantly associated with advanced TNM stage (p = 0.035), lymph node involvement (p = 0.012), and metastasis (p = 0.0003) . This pattern suggests AHA1 may serve as a prognostic marker for colorectal cancer progression.

Interestingly, mRNA expression analysis using public datasets (GSE8671 and GSE24514) confirmed increased AHA1 expression in both colorectal cancer tissues compared to normal colonic mucosa and in microsatellite instability (MSI) colorectal cancer tissues compared to normal tissues .

How do I optimize western blotting protocols for accurate AHA1 detection?

Optimizing western blot detection of AHA1 requires attention to several technical parameters:

Sample preparation:

• Include protease inhibitors (PMSF, aprotinin, leupeptin) to prevent AHA1 degradation

• Consider phosphatase inhibitors if studying phosphorylation-dependent interactions

• Use RIPA buffer for efficient extraction of both cytoplasmic and nuclear fractions

• Sonicate briefly to ensure complete lysis and DNA shearing

Electrophoresis parameters:

• Use 10-12% SDS-PAGE gels for optimal separation

• Expected molecular weight: ~38 kDa for human AHA1

• Load 20-50 μg of total protein per lane (adjust based on expression level)

• Include molecular weight markers spanning 25-50 kDa range

Transfer optimization:

• Semi-dry or wet transfer systems both work effectively

• Use PVDF membrane for better protein retention and signal

• Transfer at 100V for 60-90 minutes or 30V overnight at 4°C

• Verify transfer efficiency with Ponceau S staining

Antibody incubation:

• Block with 5% non-fat dry milk or BSA in TBST (1 hour at room temperature)

• Primary antibody dilution: typically 1:1000 (optimize based on specific antibody)

• Incubate primary antibody overnight at 4°C for maximum sensitivity

• Secondary antibody dilution: 1:5000-1:10000 (1 hour at room temperature)

Detection system:

• ECL substrates work well for moderate to high AHA1 expression

• Consider enhanced sensitivity substrates for low-abundance samples

• Optimize exposure times based on expression level (typically 30 seconds to 5 minutes)

Troubleshooting guide:

• High background: Increase blocking time, washing steps, or dilute antibody further

• No signal: Check positive controls, increase protein loading, decrease antibody dilution

• Multiple bands: Verify antibody specificity, check for degradation or post-translational modifications

Published studies successfully detected differential AHA1 expression across colorectal cancer cell lines using these approaches, revealing correlation with cancer progression .

What experimental approaches should I use to investigate AHA1's role in cancer progression?

To comprehensively investigate AHA1's involvement in cancer progression, implement these methodological approaches:

Expression analysis:

• Compare AHA1 levels between matched tumor and normal tissues using qRT-PCR and western blotting

• Correlate expression with clinical parameters (TNM stage, lymph node involvement, metastasis)

• Analyze public databases (GSE8671, GSE24514) for additional validation

• Perform immunohistochemistry to visualize spatial distribution in tissue sections

Functional studies:

• Overexpression experiments using AHA1-flag constructs in low-expressing cell lines (e.g., SW480)

• Knockdown experiments using siRNA targeting AHA1 in high-expressing cell lines (e.g., HCT116)

• Assess phenotypic changes through:

  • Wound healing assays for migration assessment

  • Transwell invasion assays with Matrigel coating

  • Cell proliferation assays (cell counting, MTT, BrdU incorporation)

Molecular pathway analysis:

• Examine EMT markers (E-cadherin, Snail) by western blot and qRT-PCR

• Assess activation of signaling pathways (pAkt, pSrc) by phospho-specific antibodies

• Investigate interaction with Hsp90 using co-immunoprecipitation

• Perform expression correlation studies between AHA1 and EMT markers

In vivo validation:

• Generate xenograft models with modified AHA1 expression

• Assess tumor growth rates, invasion, and metastatic potential

• Examine EMT marker expression in xenograft tissues

Research data demonstrates that AHA1 overexpression enhances cell migration and invasion in SW480 cells, while AHA1 knockdown reduces these capabilities in HCT116 cells . These phenotypic changes occur through regulation of EMT signaling markers including Snail (increased), E-cadherin (decreased), pAkt (increased), and pSrc (increased) .

How can I distinguish between AHA1's Hsp90-dependent and autonomous chaperone functions?

Differentiating between AHA1's dual roles requires specialized experimental approaches:

Co-immunoprecipitation studies:

• Immunoprecipitate AHA1 and probe for Hsp90 to determine proportion of AHA1 bound to Hsp90

• Perform reciprocal IP: pull down Hsp90 and detect AHA1

• Quantify the relative amounts of free versus Hsp90-bound AHA1 across different tissues and conditions

• Compare binding patterns under normal versus stress conditions

Domain-specific analysis:

• Generate AHA1 mutants lacking the N-terminal 22 amino acids (critical for autonomous function in human AHA1)

• Compare wild-type human AHA1 with yeast AHA1 (which lacks the N-terminal sequence)

• Create point mutations in the Hsp90-binding interface to disrupt specific interactions

• Test chaperone activity of each construct independently

Functional chaperone assays:

• Protein aggregation prevention assays using denatured model substrates (e.g., rhodanese)

• Compare aggregation protection capability of:

  • Full-length AHA1

  • N-terminal truncated AHA1

  • In presence/absence of Hsp90

Ubiquitination studies:

• Examine ubiquitination of client proteins in the presence of:

  • Wild-type AHA1

  • N-terminal truncated AHA1

  • AHA1 with mutations in Hsp90 binding sites

• Monitor CHIP (E3 ligase) recruitment to AHA1-client complexes

Research data indicates that the majority of AHA1 exists independent of Hsp90 as a self-contained protein in various tissues . Furthermore, AHA1 demonstrates autonomous chaperone activity, preventing aggregation of denatured proteins similar to the chaperonin GroEL . The N-terminal sequence of 22 amino acids present in human but absent from yeast AHA1 appears critical for this autonomous chaperone capability .

What methodologies are most effective for studying AHA1's involvement in epithelial-mesenchymal transition (EMT)?

To investigate AHA1's role in EMT, implement these methodological approaches:

Expression correlation studies:

• Measure AHA1 expression alongside EMT markers (E-cadherin, N-cadherin, Snail, vimentin)

• Use qRT-PCR for mRNA analysis with properly validated primers

• Employ western blotting for protein analysis with appropriate loading controls

• Perform immunofluorescence co-staining to visualize spatial relationships

Gain/loss of function experiments:

• Overexpress AHA1 in epithelial-type cancer cells (e.g., SW480)

• Knockdown AHA1 in mesenchymal-type cancer cells (e.g., HCT116)

• Assess changes in:

  • Cell morphology (phase contrast microscopy)

  • EMT marker expression (western blot, qRT-PCR)

  • Migration and invasion capabilities (wound healing, transwell invasion assays)

Signaling pathway analysis:

• Examine phosphorylation status of Akt and Src using phospho-specific antibodies

• Use inhibitors of PI3K/Akt and Src pathways to determine dependency

• Investigate transcriptional regulation of EMT-related genes (ChIP assays, reporter constructs)

• Perform time-course studies to establish signaling sequence

Rescue experiments:

• After AHA1 knockdown, reintroduce:

  • Wild-type AHA1

  • Truncated AHA1 lacking autonomous chaperone function

  • AHA1 with mutations in Hsp90 binding sites

• Determine which constructs restore EMT phenotypes

Research data shows that AHA1 regulates EMT in colorectal cancer cells through modulation of specific markers. Overexpression of AHA1 in SW480 cells decreased E-cadherin expression while increasing Snail, pAkt, and pSrc levels . Conversely, knockdown of AHA1 in HCT116 cells increased E-cadherin while decreasing Snail, pAkt, and pSrc expression . These findings establish a clear mechanistic link between AHA1 and the EMT process in colorectal cancer.

How can I effectively use AHA1 antibodies to study its role in protein quality control?

To investigate AHA1's function in protein quality control, implement these methodological approaches:

Aggregation prevention assays:

• Induce protein stress through heat shock (42°C for 1 hour), oxidative stress (H₂O₂ treatment), or proteasome inhibition (MG132)

• Isolate soluble and insoluble protein fractions by differential centrifugation

• Quantify aggregated protein levels in presence/absence of AHA1 using western blotting

• Compare cells with normal, overexpressed, or knocked-down AHA1 expression

Ubiquitination analysis:

• Immunoprecipitate AHA1 using validated antibodies and blot for ubiquitinated proteins

• Perform co-IP with CHIP (E3 ubiquitin ligase) to assess complex formation

• Use antibodies specific for K48-linked ubiquitin chains (proteasomal degradation signal)

• Conduct in vitro ubiquitination assays with purified components

Client protein identification:

• Perform mass spectrometry on AHA1-associated proteins under:

  • Normal conditions

  • Stress conditions (heat shock, oxidative stress)

  • After proteasome inhibition

• Compare client profiles between full-length and N-terminal truncated AHA1

Proteasomal degradation studies:

• Treat cells with proteasome inhibitors (MG132, bortezomib)

• Monitor accumulation of AHA1-bound client proteins

• Conduct cycloheximide chase experiments to track client protein half-lives

• Compare degradation rates in presence/absence of AHA1

Research data indicates that rather than attempting to refold bound clients, AHA1 holds them for ubiquitination by the cellular protein quality control machinery . This suggests that AHA1 functions to prevent harmful protein aggregation while facilitating the triage of damaged proteins for degradation. The N-terminal region of human AHA1 appears critical for this autonomous chaperone function .

What controls should I include when measuring AHA1 expression in cancer tissues?

When analyzing AHA1 expression in cancer tissues, incorporate these essential controls:

Technical controls:

• Positive control: Include cell line with known high AHA1 expression (HCT116)

• Negative control: Primary antibody omission on serial sections

• Isotype control: Non-specific antibody of same isotype and concentration

• Peptide competition: Pre-incubate antibody with immunizing peptide

Sample controls:

• Adjacent normal tissue from same patient (paired analysis)

• Tissue microarrays containing multiple normal tissues for baseline comparison

• Range of cancer grades/stages for expression comparison

• Include both microsatellite stable (MSS) and microsatellite instability (MSI) samples

Analytical controls:

• Housekeeping genes/proteins for normalization (GAPDH, β-actin)

• Multiple reference genes for qRT-PCR (at least 3 for stability)

• Standardized scoring system for IHC (0-3 scale as used in published research)

• Blinded scoring by multiple observers

Validation approaches:

• Multiple detection methods (qRT-PCR, western blot, IHC)

• Secondary antibody targeting different epitope

• Public dataset validation (GSE8671, GSE24514 datasets)

Research data demonstrates significantly higher AHA1 expression in colorectal cancer tissues compared to adjacent normal tissues (p = 0.032), with correlation to TNM stage (p = 0.035), lymph node metastasis (p = 0.012), and metastasis (p = 0.0003) .

How do I design experiments to investigate the interaction between AHA1 and Hsp90?

To study AHA1-Hsp90 interactions effectively, implement these experimental approaches:

Biochemical interaction studies:

• Co-immunoprecipitation: Pull down AHA1 and blot for Hsp90 isoforms (Hsp90aa1, Hsp90ab1)

• Reciprocal IP: Pull down Hsp90 and blot for AHA1

• Proximity ligation assay (PLA) for in situ visualization of interactions

• FRET analysis for live-cell interaction dynamics

Functional interaction studies:

• ATPase activity assays using purified components:

  • Purified Hsp90 alone

  • Hsp90 + wild-type AHA1

  • Hsp90 + mutant AHA1

• Client protein folding efficiency assessment using model substrates

Competition studies:

• Examine AHA1 competition with other co-chaperones (Tsc1, Fnip1)

• Determine binding preferences under different cellular conditions

• Test effects of Hsp90 inhibitors (17-AAG) on AHA1 binding

Expression correlation analysis:

• Quantify AHA1:Hsp90 ratios across different tissues and cell types

• Compare expression levels of AHA1, Hsp90aa1, and Hsp90ab1

• Analyze subcellular distribution using fractionation and immunofluorescence

• Assess redistribution under stress conditions

Structural interaction mapping:

• Generate deletion constructs to identify critical interaction domains

• Create point mutations in predicted interaction interfaces

• Perform crosslinking mass spectrometry to map contact points

Research data suggests that while AHA1 and Hsp90 interact functionally, the majority of AHA1 exists independent of Hsp90 as a self-contained protein in various tissues . The expression of Hsp90aa1 and Hsp90ab1 increases in colon cancer cells regardless of cancer grade, while AHA1 expression correlates more closely with cancer progression .

What methods should I use to study the differential roles of human versus yeast AHA1?

To investigate the functional differences between human and yeast AHA1, implement these methodological approaches:

Structural comparison analysis:

• Perform sequence alignment focusing on the N-terminal 22 amino acids unique to human AHA1

• Generate structural models of both proteins using crystallography or in silico approaches

• Design domain swapping experiments to identify functional regions

Comparative functional assays:

• Protein aggregation prevention assays with purified human and yeast AHA1

• ATPase stimulation of Hsp90 using purified components

• Client protein triage experiments comparing ubiquitination efficiency

• Yeast complementation studies with human AHA1

Chimeric protein design:

• Create human-yeast hybrid proteins:

  • Add human N-terminal sequence (22 aa) to yeast AHA1

  • Create domain-swapped variants

  • Test autonomous chaperone function of each construct

Heterologous expression systems:

• Express human AHA1 in yeast and assess functionality

• Generate mammalian cell lines with endogenous AHA1 knockdown complemented with yeast AHA1

• Compare subcellular localization patterns

Client specificity analysis:

• Identify client overlap and unique clients for each ortholog

• Compare binding affinities using purified components

• Assess functional outcomes (refolding vs. degradation facilitation)

Research data indicates that the N-terminal sequence of 22 amino acids present in human but absent from yeast AHA1 is critical for autonomous chaperone capability . This suggests an evolutionary divergence of function, with human AHA1 acquiring additional roles beyond Hsp90 ATPase activation. Understanding these differences could provide insights into the specialized functions of AHA1 in higher eukaryotes.

Why might I observe discrepancies between AHA1 mRNA and protein levels in my samples?

Discrepancies between AHA1 mRNA and protein levels could result from several biological and technical factors:

Post-transcriptional regulation:

• microRNA targeting AHA1 transcript

• RNA binding proteins affecting stability

• Alternative splicing variants producing different isoforms

Post-translational regulation:

• Protein stability differences across tissue types

• Ubiquitination and degradation rates

• Protein modifications affecting antibody recognition

Technical considerations:

• Antibody specificity and sensitivity issues

• Different detection thresholds between RNA and protein methods

• Sample processing affecting RNA or protein differently

• Storage conditions impacting protein stability

Methodological approaches to address discrepancies:

• Use multiple antibodies targeting different epitopes

• Perform protein stability assays with cycloheximide chase

• Assess post-translational modifications using specific antibodies

• Examine proteasome-dependent degradation with MG132 treatment

The research data shows that while mRNA levels of AHA1 correlate with clinicopathological characteristics in colorectal cancer, survival analysis using public datasets did not show significant association of AHA1 RNA expression with survival . This suggests complex regulation between RNA expression, protein levels, and functional outcomes that require multi-level analysis.

How can I optimize immunohistochemistry protocols for reliable AHA1 detection in tissue samples?

Optimizing IHC protocols for AHA1 detection requires attention to several key parameters:

Tissue preparation:

• Fixation: 10% neutral buffered formalin for 24 hours at room temperature

• Paraffin embedding: maintain uniform temperature control

• Section thickness: 4-5 μm for optimal antibody penetration

• Storage: freshly cut sections yield best results

Antigen retrieval optimization:

• Heat-induced epitope retrieval methods:

  • Citrate buffer (pH 6.0): 20 minutes at 95-98°C

  • EDTA buffer (pH 9.0): 20 minutes at 95-98°C

  • Test both to determine optimal condition

• Allow slides to cool gradually (20 minutes at room temperature)

Blocking parameters:

• 3-5% normal serum from secondary antibody host species (30 minutes)

• 1-3% BSA to reduce non-specific binding

• Consider hydrogen peroxide block (3% for 10 minutes) to quench endogenous peroxidase

Antibody optimization:

• Titration: Test dilutions ranging from 1:50 to 1:500

• Incubation conditions: 1 hour at room temperature or overnight at 4°C

• Diluent selection: antibody diluent with background reducing components

• Secondary antibody: use polymer-based detection for enhanced sensitivity

Visualization systems:

• DAB chromogen development: monitor under microscope for optimal signal

• Counterstain optimization: hematoxylin for 1-2 minutes

• Dehydration and mounting: use xylene-based mounting media

Controls and validation:

• Positive control tissues: colorectal cancer tissues with known AHA1 expression

• Negative controls: omit primary antibody on serial sections

• Scoring system standardization: 0-3 scale as used in published research

Research data shows successful AHA1 IHC staining in colorectal cancer tissues, with significantly increased expression in tumors (average score = 2.15) compared to adjacent normal tissues (average score = 1.35, p < 0.0001) .

What are potential pitfalls when interpreting results from AHA1 knockdown or overexpression experiments?

When designing and interpreting AHA1 manipulation experiments, be aware of these potential pitfalls:

Knockdown considerations:

• Incomplete knockdown masking phenotypes (verify >70% reduction)

• Off-target effects of siRNAs (use multiple siRNAs targeting different regions)

• Compensatory upregulation of related proteins (check AHSA2 expression)

• Timing issues (acute vs. chronic depletion effects differ)

Overexpression challenges:

• Non-physiological expression levels altering normal function

• Tag interference with protein function (compare tagged vs. untagged)

• Mislocalization due to overexpression artifacts

• Disruption of endogenous protein complexes

Experimental design recommendations:

• Use multiple siRNAs targeting different regions of AHA1 mRNA

• Include rescue experiments with siRNA-resistant constructs

• Compare transient vs. stable expression systems

• Use inducible systems for temporal control of expression

Validation approaches:

• Confirm knockdown/overexpression at both RNA and protein levels

• Assess multiple functional readouts (migration, invasion, EMT markers)

• Verify findings in multiple cell lines

• Correlate with endogenous expression patterns in tissues

Research data from AHA1 overexpression in SW480 cells and knockdown in HCT116 cells showed consistent and opposite effects on migration, invasion, and EMT marker expression . Overexpression increased migration and invasion with concurrent changes in EMT markers (decreased E-cadherin, increased Snail, pAkt, and pSrc), while knockdown produced the opposite effects . These consistent results across multiple readouts strengthen confidence in the observed phenotypes.

What are emerging areas of AHA1 research that might benefit from antibody-based approaches?

Several promising research directions for AHA1 are emerging that will benefit from antibody-based methodologies:

Therapeutic targeting potential:

• Developing antibodies that selectively disrupt AHA1-Hsp90 interactions

• Targeting the autonomous chaperone function via the N-terminal domain

• Using antibodies to block AHA1's role in cancer cell migration and invasion

• Creating antibody-drug conjugates for targeted therapy of AHA1-overexpressing tumors

Biomarker development:

• Validating AHA1 as a prognostic marker for colorectal cancer metastasis

• Developing immunoassays for clinical application

• Creating companion diagnostics for Hsp90 inhibitor therapy

• Establishing multi-parameter panels including AHA1 and EMT markers

Systems biology approaches:

• Mapping the complete AHA1 interactome beyond Hsp90

• Investigating tissue-specific roles and interactions

• Exploring the relationship between AHA1 and the ubiquitin-proteasome system

• Understanding AHA1's role in proteostasis networks

Structural biology:

• Developing antibodies for structural studies (e.g., conformation-specific antibodies)

• Mapping critical domains using epitope-specific antibodies

• Understanding the structural basis for dual functionality

• Examining conformational changes upon client binding

Research data suggests that AHA1 may serve as a potential prognostic marker associated with lymph node involvement and metastasis in colorectal cancer . Additionally, disrupting the Hsp90-AHA1 complex has been proposed as a potential therapeutic strategy to increase cancer cell sensitivity to Hsp90 inhibitors like Tanespimycin (17-AAG) .