ITGA8 Antibody

How do I select the appropriate ITGA8 antibody for my experiment?

When selecting an ITGA8 antibody, first consider your experimental application (Western blot, immunohistochemistry, flow cytometry, etc.) and target species. Current commercial antibodies show reactivity primarily to human and mouse ITGA8, with some cross-reactivity to rat, pig, and other mammalian species . For optimal results, select antibodies with validation data for your specific application. For instance, if performing Western blot analysis, prioritize antibodies demonstrating clear detection at the expected molecular weight of 117 kDa. Additionally, evaluate the antibody format (polyclonal vs. monoclonal) based on your research needs – polyclonal antibodies often provide higher sensitivity but potentially lower specificity compared to monoclonal options.

What validation methods should I use to confirm ITGA8 antibody specificity?

A comprehensive validation strategy should include multiple approaches. Begin with positive and negative control samples – tissues known to express ITGA8 (such as kidney or lung mesenchymal cells) versus those with minimal expression . For genetic validation, consider using ITGA8 knockdown/knockout samples or blocking peptides. Western blot analysis should reveal a distinct band at approximately 117 kDa, confirming antibody specificity . For immunostaining applications, compare staining patterns with published literature data, particularly the characteristic membrane localization pattern. Always include isotype controls to identify potential non-specific binding.

What sample preparation protocols optimize ITGA8 detection in Western blotting?

For optimal ITGA8 detection in Western blotting, cell or tissue lysates should be prepared using buffers containing appropriate protease inhibitors to prevent degradation of this relatively large protein. Due to its membrane localization, include 1% NP-40 or similar non-ionic detergents in your lysis buffer . For tissue samples, particularly kidney or lung, homogenization should be thorough but gentle to maintain protein integrity. Use a reducing sample buffer with DTT or β-mercaptoethanol and heat samples at 95°C for 5 minutes. When loading samples, adjust protein concentration to 20-50 μg per lane for cell lysates. During transfer, use PVDF membranes (preferred over nitrocellulose for this high molecular weight protein) and extend transfer time to ensure complete protein migration. Primary antibody concentrations typically range from 1:500 to 1:2000 dilution, but optimize based on your specific antibody's recommendations.

How can I optimize immunohistochemistry protocols for ITGA8 detection in tissue sections?

For successful ITGA8 immunohistochemistry, antigen retrieval is critical. Heat-induced epitope retrieval using citrate buffer (pH 6.0) is generally effective, with heating at 95°C for 20 minutes . For formalin-fixed paraffin-embedded (FFPE) sections, deparaffinization must be complete, followed by rehydration through graded alcohols. A blocking step using 5-10% normal serum matching the secondary antibody host is essential to reduce background. Primary antibody incubation typically works best at 4°C overnight at dilutions between 1:100 and 1:500 . For visualization, both chromogenic and fluorescent detection systems work well, though fluorescence may provide better resolution for membrane localization. When examining lung tissue specifically, co-staining with AT2 cell markers (such as SPC) can help identify ITGA8's relationship with alveolar structures . Always include a negative control by omitting the primary antibody.

What is the most effective protocol for isolating ITGA8-positive fibroblasts from lung tissue?

Isolation of ITGA8-positive fibroblasts requires a multi-step approach combining enzymatic digestion with flow cytometry sorting. Begin with fresh lung tissue dissociated using collagenase/dispase solution (2.5 mg/ml collagenase D, 2.5 mg/ml dispase, 50 U/ml DNase I in DMEM) for 45-60 minutes at 37°C with gentle agitation . Filter the resulting suspension through 70μm and then 40μm cell strainers to remove debris and undigested tissue. For FACS isolation, use a sequential gating strategy:

• Gate on viable cells (using viability dye exclusion)

• Exclude hematopoietic cells (CD45-negative)

• Select PDGFRα-positive cells (as ITGA8+ fibroblasts are a subset of PDGFRα+ fibroblasts)

• Further gate on ITGA8-positive, SCA-1-negative population

This approach yields three distinct fibroblast populations: ITGA8+SCA-1-, ITGA8-SCA-1+, and ITGA8+SCA-1+ double-positive cells . For optimal antibody staining, use concentrations of 1:100 for both anti-ITGA8 and anti-SCA-1 antibodies. This protocol typically results in >90% purity of ITGA8+ fibroblasts, which can be confirmed through post-sort analysis and LipidTOX staining, as ITGA8+ lung fibroblasts characteristically contain high levels of intracellular lipid droplets (approximately 91% positivity) .

How can I distinguish between different fibroblast subpopulations using ITGA8 as a marker?

Distinguishing between fibroblast subpopulations requires combining surface marker analysis with functional assays. ITGA8 serves as a reliable marker for alveolar lipofibroblasts within the broader PDGFRα+ fibroblast population . A comprehensive characterization approach should include:

• Surface marker panel: Use multicolor flow cytometry with antibodies against ITGA8, SCA-1 (Ly6a), PDGFRα, and additional markers like CD34 or PDPN to identify distinct subpopulations.

• Lipid content analysis: Stain cells with LipidTOX or Oil Red O to quantify lipid droplet content. ITGA8+ fibroblasts typically show significantly higher lipid content (91.0±1.5%) compared to SCA-1+ fibroblasts (5.0±0.5%) .

• Transcriptome profiling: Analyze expression of lipofibroblast-associated genes including Tcf21 and Plin2, which are significantly upregulated in ITGA8+ fibroblasts.

• Spatial analysis: Use immunofluorescence to map the distribution of different fibroblast subpopulations, noting that ITGA8+ fibroblasts predominantly localize to alveolar regions, often adjacent to alveolar epithelial type 2 (AT2) cells .

• Functional assays: Evaluate niche supporting capacity through alveolar organoid co-culture experiments to assess functional differences between ITGA8+ and SCA-1+ fibroblasts.

This multi-parameter approach enables reliable discrimination between lipofibroblasts (ITGA8+) and other fibroblast subpopulations, with both populations showing distinct molecular signatures and functional properties.

How should I design experiments to investigate the interaction between ITGA8+ fibroblasts and alveolar epithelial cells?

Designing experiments to investigate ITGA8+ fibroblast interactions with alveolar epithelial cells requires multiple complementary approaches:

• Co-culture systems: Establish direct co-culture models using FACS-isolated ITGA8+ fibroblasts and primary AT2 cells or AT2-like cell lines. Compare with ITGA8- fibroblast populations as controls. Analyze cell morphology, proliferation rates, and epithelial marker expression over 7-14 days.

• Organoid formation assay: Use a 3D Matrigel-based alveolar organoid assay with AT2 cells (isolated from reporter mice like Sftpc-creERT2; tdTomato) co-cultured with ITGA8+ fibroblasts . Quantify organoid number, size, and branching complexity after 14-21 days in culture. This approach revealed that, surprisingly, ITGA8+ fibroblasts show lower efficiency in supporting alveolar organoid formation compared to SCA-1+ fibroblasts, despite their proximity to AT2 cells in vivo .

• Conditioned media experiments: Collect conditioned media from ITGA8+ fibroblast cultures and apply to AT2 monocultures to assess paracrine signaling effects. Analyze surfactant production, proliferation markers, and differentiation status.

• Transcriptome analysis: Compare gene expression profiles between AT2 cells cultured alone versus those co-cultured with ITGA8+ fibroblasts, focusing on pathways related to surfactant production, proliferation, and differentiation.

• Functional assays: Measure lipid transfer between ITGA8+ fibroblasts and AT2 cells using fluorescently labeled lipids and live imaging techniques.

When interpreting results, consider that ITGA8+ fibroblasts show higher expression of potential AT2-supportive factors including Fgf10, Fgf7, and Wnt2 compared to SCA-1+ fibroblasts, yet their organoid-forming capacity is lower , suggesting complex regulatory mechanisms beyond simple growth factor production.

What are the most common technical challenges in detecting ITGA8 and how can they be overcome?

Several technical challenges can complicate ITGA8 detection in research settings:

• Low signal intensity: ITGA8 expression levels can vary considerably between tissues and cell types. To enhance detection:

  • Increase antibody concentration (titrate from 1:100 to 1:500)

  • Extend primary antibody incubation time (overnight at 4°C)

  • Use signal amplification methods such as tyramide signal amplification for IHC/IF

  • For Western blotting, load higher protein concentrations (50-80μg) and use enhanced chemiluminescence substrates

• Background staining: Non-specific binding can obscure true ITGA8 signal. Address this by:

  • Extending blocking time (2 hours at room temperature) with 5% BSA or 10% normal serum

  • Including 0.1-0.3% Triton X-100 in blocking buffer for better antibody penetration

  • Using control IgG at the same concentration as the ITGA8 antibody

  • Performing antigen pre-absorption controls with the immunizing peptide

• Sample preparation issues: As a membrane protein, ITGA8 detection is sensitive to fixation conditions:

  • For FFPE tissues, limit fixation time to 24 hours maximum

  • For fresh tissues, use 4% PFA for 2-4 hours followed by cryoprotection

  • For cell lines, 10-minute fixation with 4% PFA is typically sufficient

  • Include membrane permeabilization steps with careful optimization

• Antibody specificity concerns: Validate specificity through:

  • ITGA8 knockdown controls using siRNA

  • Peptide competition assays

  • Comparison of staining patterns across multiple antibodies targeting different ITGA8 epitopes

• Detection in flow cytometry: Membrane proteins can be challenging in flow applications:

  • Avoid harsh enzymatic dissociation methods that might cleave surface proteins

  • Use gentler cell dissociation reagents (Accutase instead of trypsin)

  • Optimize staining buffer composition (include 2% FBS and 2mM EDTA)

  • Perform staining at 4°C to prevent internalization

By systematically addressing these challenges, researchers can significantly improve ITGA8 detection reliability across multiple experimental platforms.

How can transcriptome profiling be used to characterize ITGA8+ cell populations in different disease contexts?

Transcriptome profiling offers powerful insights into ITGA8+ cell populations across disease contexts. An effective approach includes:

When interpreting transcriptome data, consider that ITGA8 expression itself may be regulated by disease processes. For example, in fibrotic conditions, the proportion and gene expression profile of ITGA8+ fibroblasts may change significantly, reflecting their potential roles in pathological tissue remodeling.

What experimental approaches can determine the functional significance of ITGA8 in fibroblast-epithelial interactions during tissue repair?

Understanding the functional significance of ITGA8 in fibroblast-epithelial interactions during tissue repair requires multiple complementary experimental approaches:

• Conditional knockout models: Generate fibroblast-specific ITGA8 knockout mice using Cre-LoxP technology (e.g., Pdgfra-Cre;ITGA8-flox) to assess the impact on epithelial regeneration following tissue injury. Analyze repair kinetics, fibrosis development, and restoration of normal tissue architecture.

• In vitro wound healing assays: Establish co-culture systems with epithelial cells and either ITGA8-expressing or ITGA8-depleted fibroblasts separated by a scratch wound. Measure wound closure rates, epithelial migration, and proliferation markers to assess the impact of ITGA8 on repair processes.

• Organoid injury models: Develop alveolar organoids using AT2 cells co-cultured with ITGA8+ fibroblasts, then introduce controlled injury (e.g., bleomycin exposure). Compare regenerative responses between organoids with normal ITGA8+ fibroblasts versus those with ITGA8-knockdown fibroblasts .

• Mechanistic dissection: Use blocking antibodies against specific domains of ITGA8 to identify which structural regions mediate key functional interactions. Complement with biochemical approaches to identify binding partners critical for repair functions.

• Signal pathway analysis: Investigate how ITGA8 expression affects key regenerative signaling pathways, particularly:

  • TGF-β pathway activation (known to be regulated by integrins)

  • WNT signaling (ITGA8+ fibroblasts express higher levels of Wnt2)

  • FGF pathway activity (given the expression of Fgf7/Fgf10 in these cells)

• Lineage tracing experiments: Use genetic lineage tracing (ITGA8-CreERT2) to follow the fate of ITGA8+ fibroblasts during injury and repair, determining whether they expand, differentiate, or adopt alternative phenotypes.

• Extracellular matrix analysis: Compare ECM production and remodeling between ITGA8+ and ITGA8- fibroblasts during repair, as integrin-mediated interactions with the ECM likely influence repair processes.

These approaches together can determine whether ITGA8 simply serves as a marker of fibroblast subpopulations or plays a functional role in mediating repair processes through direct or indirect effects on epithelial regeneration.