CD34 Monoclonal Antibody,PE Conjugated

What is CD34 and why is it an important research target?

CD34 is a 115 kDa glycoprotein expressed on multipotent precursors, bone marrow stromal cells, embryonic fibroblasts, and vascular endothelia. It functions as a possible adhesion molecule with a crucial role in early hematopoiesis, mediating the attachment of stem cells to the bone marrow extracellular matrix or directly to stromal cells. Additionally, CD34 may serve as a scaffold for the attachment of lineage-specific glycans, enabling stem cells to bind to lectins expressed by stromal cells or other marrow components. Its selective expression pattern makes it an invaluable marker for identifying and isolating hematopoietic stem and progenitor cells in various research contexts.

What are the primary research applications for CD34 PE-conjugated antibodies?

CD34 PE-conjugated antibodies serve multiple research functions across immunology, hematology, and oncology fields. They are primarily validated for flow cytometry applications, enabling identification and quantification of hematopoietic progenitor cells. These antibodies are instrumental in diagnosing hematologic malignancies, solid tumors, and immunodeficiency diseases. Additionally, they facilitate isolation of hematopoietic progenitor cells, disease monitoring, and in vitro differentiation studies. In recent applications, they have been used in CAR-T cell research as marker genes for transduced cells.

How do monoclonal CD34 antibodies differ from polyclonal antibodies in research applications?

Monoclonal CD34 antibodies, such as clone QBEnd10, offer superior specificity through recognition of precisely defined epitopes on the CD34 antigen. This precise targeting results in more consistent experimental outcomes and reduced background noise compared to polyclonal alternatives. Monoclonal antibodies provide uniform binding characteristics across experiments, allowing for standardized protocols and comparable results between different research groups. Conversely, polyclonal CD34 antibodies recognize multiple epitopes across the CD34 protein (as evidenced by broader immunogen ranges like 301-385/385), potentially offering higher sensitivity but with increased variability. The choice between these antibody types should be guided by specific experimental requirements—monoclonals for precision and reproducibility, polyclonals when broader epitope recognition may be advantageous.

What are the optimal conditions for using CD34 PE-conjugated antibodies in flow cytometry?

For optimal flow cytometry results with CD34 PE-conjugated antibodies, prepare single-cell suspensions with 1-5×10^6 cells/mL in appropriate buffer (typically PBS with 0.5-2% protein blocking agent and 0.1% sodium azide). Use approximately 10 μL of antibody per 10^6 cells for human peripheral blood mononuclear cells (PBMCs). Incubate for 15-30 minutes at 2-8°C in the dark to prevent photobleaching of the PE fluorophore (excitation = 488 nm, emission = 565-605 nm). Always include appropriate isotype controls (such as Mouse IgG1, catalog # IC002P) for accurate gating. For multicolor flow cytometry, CD34 PE antibodies can be effectively combined with other markers such as CD45 Alexa Fluor 700 to facilitate proper identification of rare progenitor populations. Following staining, wash cells twice with buffer before analysis to reduce background fluorescence. Optimal antibody concentration should be determined by titration for each specific application and cell type.

How should researchers validate the specificity of CD34 PE-conjugated antibodies?

Validation of CD34 PE-conjugated antibody specificity requires a multi-parameter approach. First, establish positive and negative controls—KG-1a human acute myelogenous leukemia cell line serves as an excellent positive control as it expresses high levels of CD34, while differentiated lymphocytes can serve as negative controls. Compare staining patterns between the antibody of interest (e.g., FAB7227P) and corresponding isotype controls to identify non-specific binding. For human samples, conduct blocking experiments using unconjugated CD34 antibodies to confirm epitope specificity. Additionally, validate with orthogonal techniques like Western blotting or ELISA using CD34 peptides where appropriate. When assessing novel cell populations, consider performing comparative analyses with established CD34 antibody clones (such as QBEnd10) that recognize distinct epitopes. Document consistent staining patterns across multiple donor samples to account for biological variability.

What are the critical considerations for long-term storage of CD34 PE-conjugated antibodies to maintain functionality?

Preserving the functionality of CD34 PE-conjugated antibodies requires strict adherence to storage protocols. These antibodies must be protected from light at all times to prevent photobleaching of the PE fluorophore. Store at 2-8°C for up to 12 months from the date of receipt as specified by manufacturers. Never freeze these conjugates as freeze-thaw cycles can compromise the PE fluorophore's structural integrity and quantum yield. For longer-term storage, aliquoting into smaller volumes is essential to avoid repeated freeze-thaw cycles. Storage buffers typically contain stabilizers such as BSA (1%) and sodium azide as a preservative, which should be maintained during any dilution procedures. Prior to each use, centrifuge the antibody solution briefly to collect liquid at the bottom of the vial. Regular quality control testing on standard cell types (like KG-1a cells) is recommended to verify staining efficiency over time, particularly for antibodies approaching their expiration date.

How can researchers address weak or absent CD34 staining in flow cytometry experiments?

Weak or absent CD34 staining can result from multiple factors requiring systematic troubleshooting. First, verify antibody viability by testing on a positive control like KG-1a cells, which consistently express high CD34 levels. If the control staining is suboptimal, the antibody may have degraded due to improper storage (exposure to light or temperature fluctuations). For fresh samples, inadequate staining may result from epitope masking during processing—adjust fixation protocols or try alternative clones recognizing different epitopes. Insufficient antibody concentration is another common issue; perform titration experiments to determine optimal concentration for your specific cell type. For rare CD34+ populations, increase cell numbers analyzed (minimum 500,000 events) and implement a CD45/SSC gating strategy to enrich for progenitor populations before analyzing CD34 expression. Additionally, ensure compensation settings are correctly established for PE in multicolor panels to prevent spillover from other fluorophores masking genuine CD34 signal.

What strategies can be employed to reduce background when using CD34 PE-conjugated antibodies in various applications?

Reducing background with CD34 PE-conjugated antibodies requires a multi-faceted approach. Implement robust blocking protocols using 2-5% serum from the same species as the secondary antibody (if applicable) or commercial blocking buffers containing irrelevant proteins. For flow cytometry, always incorporate Fc receptor blocking reagents before antibody incubation, particularly when working with samples containing high numbers of Fc receptor-expressing cells such as monocytes or macrophages. Optimize incubation times and temperatures—longer incubations at 4°C often reduce non-specific binding compared to room temperature protocols. Ensure thorough washing steps (at least two washes with excess buffer) following staining. Always run parallel samples with isotype control antibodies (Mouse IgG for QBEnd10 clone) at the same concentration as the CD34 antibody to distinguish specific from non-specific signals. For imaging applications, autofluorescence can be minimized by including a brief incubation with 0.1% Sudan Black B in 70% ethanol after fixation. When analyzing samples with potential endogenous biotin, use biotin-blocking systems before applying any biotinylated detection reagents.

How should researchers interpret discrepancies between CD34 expression levels detected by different antibody clones?

Discrepancies in CD34 expression levels between different antibody clones often reflect epitope-specific biological phenomena rather than technical errors. The CD34 molecule contains distinct epitopes classified into three classes based on their sensitivity to enzymatic cleavage and glycosylation patterns. Class I epitopes (recognized by clones like ICH3) are sensitive to neuraminidase, while Class II epitopes (recognized by QBEnd10) resist neuraminidase but are sensitive to glycoprotease. Class III epitopes resist both enzymes. Therefore, differential glycosylation across cell types or developmental stages can make certain epitopes inaccessible to specific clones. When encountering discrepancies, researchers should first verify technical aspects (antibody concentration, fluorophore brightness, instrument settings) are comparable. Subsequently, characterize the specific epitope class recognized by each clone and consider whether sample processing might differentially affect epitope accessibility. Cross-validation with antibodies recognizing different epitope classes or orthogonal techniques (like qPCR for CD34 mRNA) can help distinguish technical from biological variations. These discrepancies themselves may reveal important biological insights about post-translational modifications of CD34 in different cellular contexts.

How can CD34 PE-conjugated antibodies be effectively utilized in CAR-T cell research?

CD34 PE-conjugated antibodies serve multiple sophisticated functions in CAR-T cell research frameworks. As demonstrated in recent studies, truncated CD34 can be co-expressed with chimeric antigen receptors (CARs) as a marker gene, enabling precise identification and isolation of successfully transduced T cells. This approach facilitates critical analyses of CAR-T cell functionality including proliferation assessment through CFSE dilution experiments comparing CD34+ (transduced) versus CD34- (non-transduced) populations within the same culture. For this application, researchers should implement a hierarchical gating strategy first identifying viable T cells through appropriate scatter and viability dye parameters, then separating CD34+ from CD34- subsets before analyzing functional readouts (proliferation, cytokine production, cytotoxicity). When designing vectors, ensure the CD34 marker is co-expressed with the CAR construct using self-cleaving peptides (like P2A) for equimolar expression. This approach allows direct correlation between CD34 expression intensity and CAR density, facilitating dose-response studies of receptor density versus functional outcomes. Additionally, CD34 labeling enables in vivo tracking of CAR-T persistence in preclinical models through serial blood sampling and flow cytometric analysis.

What are the methodological considerations for using CD34 PE-conjugated antibodies in identifying and isolating tissue-resident stem cells beyond hematopoietic populations?

When employing CD34 PE-conjugated antibodies to identify non-hematopoietic stem cell populations, researchers must implement specific methodological refinements. Since CD34 expression extends to vascular endothelial cells and certain tissue fibroblasts, implement multi-parameter analysis combining CD34 with tissue-specific markers to distinguish stem cells from other CD34+ populations. For adipose-derived stem cells, combine CD34 with CD31-negative gating to exclude endothelial contamination. When isolating dental pulp stem cells, pair CD34 with STRO-1 for enhanced purification. Tissue digestion protocols require careful optimization, as excessive enzymatic treatment can cleave CD34 epitopes—use collagenase concentrations below 0.1% and include protease inhibitors when possible. For microscopy applications in solid tissues, perform dual immunofluorescence with vascular markers (CD31/vWF) to distinguish vascular versus stem cell CD34 expression. When isolating cells for functional studies, consider implementing magnetic-activated cell sorting (MACS) before flow cytometry to enrich rare CD34+ populations. Finally, since CD34 expression can fluctuate based on culture conditions and passage number in many tissue-resident stem cells, standardize analysis timepoints relative to isolation and culture conditions to ensure comparable results across experiments.

How can researchers effectively use CD34 PE-conjugated antibodies in multiplexed immunophenotyping panels for rare cell detection?

Developing effective multiplexed panels incorporating CD34 PE-conjugated antibodies for rare cell detection requires strategic fluorophore selection and panel design. Position PE-conjugated CD34 antibodies as a cornerstone marker due to PE's exceptional brightness (quantum yield), which enhances detection sensitivity for rare populations. Implement a minimum of 16-parameter panels including viability dye, CD45, lineage markers (CD3, CD19, CD56, CD14), and additional progenitor markers (CD38, CD90, CD133) alongside CD34-PE for comprehensive characterization. For optimal compensation, select fluorochromes with minimal spectral overlap with PE (565-605nm emission range)—ideal partners include BV421, APC, and AF700. When analyzing rare populations (<0.1% of total events), collect minimum 1-2 million total events and implement sequential gating: first excluding doublets and dead cells, then using CD45/SSC properties to identify candidate progenitor regions before examining CD34 expression. Consider using computational approaches like viSNE or SPADE for high-dimensional analysis of complex CD34+ subpopulations. For extreme rare event analysis (e.g., circulating tumor cells), implement pre-enrichment using either density gradient separation or magnetic bead selection for CD34+ cells before detailed flow cytometric analysis to increase detection sensitivity while reducing acquisition time.

What statistical approaches are recommended for analyzing flow cytometry data from CD34 PE-conjugated antibody experiments?

Statistical analysis of flow cytometry data derived from CD34 PE-conjugated antibody experiments requires specialized approaches reflecting the unique properties of these datasets. For quantifying CD34+ populations, report both percentage (relative to appropriate parent population) and absolute count (cells/μL) when possible, as these measures may diverge in disease states. When defining CD34+ versus CD34- populations, employ objective thresholding methods rather than arbitrary gates—the robust negative control-based method using isotype controls (e.g., Mouse IgG1-PE, IC002P) or fluorescence-minus-one (FMO) controls provides more reproducible results than visual gating. For rare CD34+ populations (<1% of total), calculate the staining index (SI = [MFI positive - MFI negative]/[2 × SD of negative]) to objectively assess separation quality. For multi-center studies, implement standardized protocols with rainbow calibration particles to normalize MFI values across instruments and time points. For analyzing heterogeneous CD34+ subpopulations, apply dimension reduction techniques like tSNE or UMAP followed by density-based clustering. When correlating CD34 expression with clinical outcomes, use appropriate non-parametric tests (Spearman correlation, Mann-Whitney U) as CD34 expression data typically follows non-normal distributions. Report both effect sizes and p-values to demonstrate both statistical and biological significance.

How can researchers accurately interpret variations in CD34 staining intensity in relation to stem cell functionality?

Interpreting variations in CD34 staining intensity requires nuanced analysis linking expression levels to functional properties. CD34 staining intensity (measured as median fluorescence intensity, MFI) often correlates inversely with hematopoietic stem cell maturation—the brightest CD34+ cells (CD34++) typically represent more primitive progenitors with enhanced self-renewal capacity. To properly investigate this relationship, researchers should fractionate cells based on CD34 expression quartiles and perform parallel functional assays including colony-forming unit (CFU) assays, long-term culture-initiating cell (LTC-IC) assays, and in vivo repopulation studies. Changes in glycosylation patterns during differentiation can affect epitope accessibility for certain antibody clones, potentially creating discrepancies between apparent expression levels and actual protein abundance. Therefore, complementary approaches such as transcript analysis or using multiple antibody clones recognizing distinct epitopes can provide more comprehensive assessment. Microenvironmental factors including hypoxia, inflammatory cytokines, and cell-cell interactions can transiently modulate CD34 expression without permanent changes in cell identity—researchers should standardize collection and processing conditions to minimize these artifacts. Finally, interlaboratory standardization using commercially available calibration beads with defined numbers of PE molecules allows conversion of arbitrary MFI units to absolute molecules of equivalent soluble fluorochrome (MESF) values, enabling more direct comparison of staining intensities across experiments and research groups.

What are the critical considerations when comparing data obtained using different CD34 antibody clones or fluorochrome conjugates?

When comparing data generated using different CD34 antibody clones or fluorochrome conjugates, researchers must account for multiple variables that influence apparent expression levels. Different monoclonal antibodies (e.g., QBEnd10 versus other clones) recognize distinct epitopes on the CD34 molecule which may be differentially accessible depending on glycosylation status, protein conformation, or sample preparation methods. To address this, perform parallel staining of identical samples with multiple clones to establish correlation factors. Fluorochromes exhibit varying quantum yields and staining indices—PE conjugates typically demonstrate 5-10 fold higher sensitivity than FITC conjugates for detecting low-density antigens. When transitioning between fluorochromes, implement fluorescence calibration beads to normalize data to absolute units (MESF). Antibody binding capacity can also vary between lots even within the same clone and conjugate; maintain consistent lot usage for longitudinal studies or implement lot-specific calibration curves. Different flow cytometers employ distinct optical configurations affecting sensitivity and resolution—use standardized particles to normalize instrument performance when comparing data across platforms. Finally, data analysis algorithms significantly impact reported percentages of CD34+ cells; standardize gating strategies and analysis templates, preferably employing automated gating approaches to minimize investigator bias. These considerations are particularly critical for clinical applications where CD34 quantification informs treatment decisions.

Research Applications Table: CD34 PE-Conjugated Antibody Protocol Parameters