AKT2 (Ab-474) Antibody

What epitope does the AKT2 (Ab-474) Antibody recognize?

The AKT2 (Ab-474) Antibody recognizes a peptide sequence around amino acids 472-476 (Q-F-S-Y-S) derived from human AKT2 . This region is located near the critical S474 phosphorylation site, which is important for AKT2 function. The antibody was produced by immunizing rabbits with this synthetic peptide conjugated to KLH (keyhole limpet hemocyanin) and subsequently purified using affinity chromatography with epitope-specific peptide .

What applications is the AKT2 (Ab-474) Antibody validated for?

The AKT2 (Ab-474) Antibody has been validated for multiple research applications including:

• Western Blot (WB): Recommended dilution of 1:500-1:1000

• Immunohistochemistry (IHC): Recommended dilution of 1:50-1:200

• Enzyme-Linked Immunosorbent Assay (ELISA)

The antibody has demonstrated reactivity with human, mouse, and rat samples, making it suitable for cross-species studies .

How should the AKT2 (Ab-474) Antibody be stored and handled?

For optimal performance and longevity, store the antibody at -20°C for long-term preservation or at 4°C for short-term use. The antibody is supplied at a concentration of 1.0 mg/mL in phosphate-buffered saline (without Mg²⁺ and Ca²⁺), pH 7.4, containing 150mM NaCl, 0.02% sodium azide, and 50% glycerol . Avoid repeated freeze-thaw cycles as these can degrade antibody quality and performance.

What is the significance of AKT2 in cellular signaling?

AKT2 is one of three members (AKT1, AKT2, and AKT3) of the serine/threonine kinase subfamily also known as Protein Kinase B. AKT2 plays pivotal roles in:

• Cell survival and growth signaling

• Glucose metabolism and insulin signaling

• Migration and invasion in various cell types

• Regulation of lysosomal function and autophagy

AKT2 is activated through phosphorylation in a PI3K-dependent manner, with full activation requiring phosphorylation at both threonine 309 in the activation loop and serine 474 in the C-terminal activation domain .

How can I optimize Western blot protocols for detecting AKT2 phosphorylation status?

When designing Western blot experiments to detect AKT2 phosphorylation:

• Sample preparation: Include phosphatase inhibitors (e.g., sodium orthovanadate, sodium fluoride) in your lysis buffer to prevent dephosphorylation during extraction.

• Control samples: Include both positive controls (insulin-stimulated samples for S474 phosphorylation) and negative controls (samples treated with PI3K inhibitors like wortmannin).

• Antibody selection: Use phospho-specific antibodies for S474 or T309 alongside the total AKT2 (Ab-474) Antibody to determine phosphorylation ratios.

• Stripping and reprobing: When using multiple antibodies, optimize stripping protocols to ensure complete removal of initial antibodies without protein loss.

• Quantification: Normalize phospho-AKT2 signal to total AKT2 rather than housekeeping proteins to account for expression level variations .

What are recommended protocols for studying AKT2 in insulin signaling experiments?

For investigating AKT2's role in insulin signaling:

• Cell model selection: Adipocytes, myocytes, or hepatocytes are appropriate models. L6 myoblasts and 3T3-L1 adipocytes are well-established cell lines.

• Insulin stimulation: After serum starvation (4-6 hours), stimulate cells with insulin (typically 100 nM) for 10-30 minutes.

• Inhibitor studies: To distinguish AKT2-specific effects, use isoform-selective inhibitors or siRNA knockdown approaches targeting specific AKT isoforms.

• Readouts: Measure downstream effects on:

  • Glucose uptake using radiolabeled glucose

  • GLUT4 translocation via cell surface biotinylation or immunofluorescence

  • Phosphorylation of downstream targets like AS160 or GSK3β

Studies have demonstrated that phosphorylation of AKT2 at T309 is necessary for insulin-stimulated GLUT4 translocation, while S474 phosphorylation is dispensable for this specific function but required for other AKT2-mediated processes .

How can I design co-immunoprecipitation experiments to identify novel AKT2 binding partners?

Based on protocols that successfully identified novel AKT2 interactions:

• Pre-clearing: Pre-clear cell lysates with non-specific IgG to reduce non-specific binding.

• Immunoprecipitation conditions:

  • Use 500-1000 μg of total protein per IP reaction

  • Incubate with 2-5 μg AKT2 (Ab-474) Antibody overnight at 4°C

  • Capture with Protein A/G beads for 2-4 hours

• Controls: Include non-specific IgG immunoprecipitation and input samples.

• Washing: Perform stringent washes (at least 4-5 times) with buffers containing 150-300mM NaCl.

• Detection methods:

  • For known interactions: Western blot with antibodies against suspected partners

  • For novel interactions: MS/MS analysis following 1D-SDS-PAGE separation

• Quantification: Normalize peak areas of identified proteins against AKT2 peak area, as shown in this example data table from insulin stimulation studies:

This approach revealed that insulin stimulation increased ROCK2 association with AKT2 approximately 6.6-fold .

How can I distinguish between the roles of different AKT isoforms using the AKT2 (Ab-474) Antibody?

To delineate isoform-specific functions:

• Complementary approaches: Combine the AKT2 (Ab-474) Antibody with genetic approaches (siRNA, CRISPR-Cas9) targeting specific AKT isoforms.

• Isoform-specific substrates: Monitor phosphorylation of substrates preferentially regulated by AKT2 versus AKT1 or AKT3.

• Rescue experiments: In AKT2-depleted cells, express phospho-mutants (T309A, S474A, or S474D) to determine which phosphorylation sites are critical for specific functions.

• Spatial distribution analysis: Use immunofluorescence with the AKT2 (Ab-474) Antibody to examine subcellular localization differences between isoforms.

Research has demonstrated that while AKT isoforms share significant homology, they have distinct functions. For example, in melanoma, AKT2 depletion specifically impaired cell migration and invasion without affecting proliferation or viability, while AKT1 or AKT3 depletion did not impact these metastasis-related functions .

What are the considerations for investigating AKT2 S474 phosphorylation in substrate selection studies?

When studying how S474 phosphorylation affects AKT2 substrate selection:

• Phospho-mutant analysis: Generate cells expressing AKT2-S474A (non-phosphorylatable) or AKT2-S474D (phosphomimetic) mutants.

• Domain deletion studies: Compare the activities of:

  • Full-length AKT2

  • AKT2 without the hydrophobic motif (HM) domain containing S474

  • AKT2 without the PH domain

• Substrate-specific assays: Evaluate different AKT2 substrates to determine phosphorylation dependencies:

  • FOXO1/3 phosphorylation is often dependent on S474 phosphorylation

  • GSK3β phosphorylation may be less dependent on S474 phosphorylation

• Context-specific effects: Consider cellular context, as research has shown that S474 phosphorylation requirements differ between processes:

  • GLUT4 translocation in adipocytes is independent of S474 phosphorylation

  • GLUT1-mediated glucose uptake requires S474 phosphorylation

These context-dependent requirements highlight the role of mTORC2-mediated S474 phosphorylation in AKT2 substrate selection and function .

How can the AKT2 (Ab-474) Antibody be used in studies of disease models?

For disease model applications:

• Cancer research: Use the antibody to:

  • Compare AKT2 expression and phosphorylation between primary and metastatic samples

  • Monitor effects of PI3K/AKT pathway inhibitors on AKT2 activation

  • Evaluate AKT2's role in migration and invasion using wound healing and transwell assays

• Metabolic disease models: Apply in:

  • Insulin resistance studies in adipocytes or muscle cells

  • Liver samples from metabolic syndrome or diabetes models

  • Pancreatic β-cell function and survival studies

• Neurodegenerative conditions: Investigate in:

  • Age-related macular degeneration models, where AKT2 overexpression in RPE cells created a dry AMD-like phenotype in mice

  • AKT2's role in lysosomal function via the AKT2/SIRT5/TFEB pathway

Research has shown that the AKT2/SIRT5/TFEB pathway may be a potential therapeutic target in age-related macular degeneration, as increased AKT2 inhibits PGC-1α to downregulate SIRT5, disrupting TFEB-dependent lysosomal function in the retinal pigmented epithelium .

How do I interpret conflicting phosphorylation data in AKT2 signaling studies?

When facing contradictory results:

• Context considerations: Phosphorylation patterns may differ between:

  • Cell types (e.g., adipocytes vs. cancer cells)

  • Stimuli (insulin vs. growth factors vs. stress signals)

  • Disease states (normal vs. pathological)

• Cross-reactivity assessment: Confirm antibody specificity, as phospho-antibodies may cross-react with other AKT isoforms due to sequence homology around phosphorylation sites.

• Temporal dynamics: Consider timing of phosphorylation events:

  • T309 and S474 phosphorylation may occur independently

  • Different sites may have different kinetics and persistence

• Phosphorylation interdependence: Research indicates T309 phosphorylation is not a prerequisite for S474 phosphorylation and vice versa, as demonstrated in insulin-stimulated phosphorylation studies .

What experimental variables might affect detection of AKT2 with the Ab-474 antibody?

Key factors that may influence antibody performance include:

• Sample preparation: Variations in:

  • Lysis buffer composition (detergent type and concentration)

  • Protein denaturation methods (heat vs. chemical)

  • Sample storage conditions and freeze-thaw cycles

• Phosphorylation status: Since the Ab-474 epitope (aa 472-476) is near the S474 phosphorylation site, phosphorylation might affect antibody binding.

• Protein interactions: Protein-protein interactions involving the C-terminal region may mask the epitope.

• Experimental conditions:

  • Blocking reagents (BSA vs. milk)

  • Incubation times and temperatures

  • Secondary antibody selection and optimization

• Species variations: While the antibody is reported to work with human, mouse, and rat samples, sequence variations around the epitope may affect performance across species.

How can I reconcile AKT2 functional data between in vitro and in vivo models?

When integrating findings across experimental systems:

• Model-specific differences: Consider:

  • Cell lines vs. primary cells vs. tissues

  • Acute vs. chronic manipulations of AKT2

  • Compensatory mechanisms in knockout models

• AKT2 expression levels: Evaluate whether:

  • Overexpression systems may cause non-physiological effects

  • Partial knockdown may produce different results than complete knockout

• Combinatorial signaling: Assess interactions with:

  • Other AKT isoforms that may compensate for AKT2 loss

  • Parallel signaling pathways that may amplify or attenuate AKT2 effects

• Validation strategies:

  • Use multiple approaches (genetic, pharmacological, and antibody-based)

  • Confirm key findings in more physiologically relevant systems

Research in Akt2 KI mice demonstrated that AKT2 overexpression in RPE cells caused a dry AMD-like phenotype in aging mice, validating observations made in cell culture models regarding the AKT2/SIRT5/TFEB pathway's role in RPE function .

How might the AKT2 (Ab-474) Antibody be applied in studies of novel AKT2 binding partners?

For investigating new protein interactions:

• Proximity labeling approaches: Combine with BioID or APEX2 techniques to identify proteins in close proximity to AKT2 in living cells.

• Multi-antibody IP strategies: Use sequential immunoprecipitation with the AKT2 (Ab-474) Antibody followed by phospho-specific antibodies to isolate specific AKT2 subpopulations.

• Crosslinking MS studies: Employ chemical crosslinking followed by mass spectrometry to capture transient interactions.

• Domain-specific interactions: Investigate whether proteins interact specifically with regions near the Ab-474 epitope (aa 472-476).

• Stimulus-dependent interactions: Recent studies identified stimulus-dependent AKT2 interactions, such as increased ROCK2 association following insulin stimulation, with normalized peak area ratios increasing from 7.67E-05 in basal conditions to 5.05E-04 after insulin treatment .

What are the implications of AKT2 phosphorylation heterogeneity for targeted therapies?

When considering therapeutic targeting:

• Site-specific inhibition: Design strategies targeting:

  • T309 phosphorylation for metabolic disorders

  • S474 phosphorylation for cancer applications

  • Substrate-specific interfaces for selective pathway inhibition

• Combination approaches: Consider targeting:

  • Upstream activators (PI3K, PDK1, mTORC2) alongside AKT2

  • Downstream effectors in a context-dependent manner

• Biomarker development: Use the AKT2 (Ab-474) Antibody to:

  • Evaluate total and phospho-AKT2 ratios as predictive biomarkers

  • Monitor treatment response in patient samples

• Resistance mechanisms: Investigate how alterations in AKT2 phosphorylation contribute to therapy resistance, particularly in cancers where AKT2 depletion impairs metastatic potential .

How can systems biology approaches integrate AKT2 phosphorylation data with broader signaling networks?

For systems-level analysis:

• Phosphoproteomics integration: Combine AKT2 (Ab-474) Antibody-based studies with global phosphoproteomic data to:

  • Map kinase-substrate relationships

  • Identify feedback mechanisms

  • Discover novel nodes in AKT2-dependent networks

• Temporal signaling dynamics: Develop time-course experiments to understand:

  • Order of phosphorylation events

  • Signal persistence and adaptation

  • Threshold effects in downstream pathway activation

• Computational modeling: Integrate experimental data into:

  • Ordinary differential equation models of AKT pathway dynamics

  • Bayesian networks predicting AKT2 substrate selection

  • Agent-based models of cellular phenotypes

• Multi-omics approaches: Correlate AKT2 phosphorylation status with:

  • Transcriptomic changes

  • Metabolomic alterations, particularly in glucose metabolism

  • Changes in protein-protein interaction networks