DRB3 Antibody

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Product Specs

Buffer
Preservative: 0.03% Proclin 300
Composition: 50% Glycerol, 0.01M Phosphate Buffered Saline (PBS), pH 7.4
Form
Liquid
Lead Time
Made-to-order (14-16 weeks)
Synonyms
DRB3 antibody; Os05g0307400 antibody; LOC_Os05g24160 antibody; Double-stranded RNA-binding protein 3 antibody; dsRNA-binding protein 3 antibody
Target Names
DRB3
Uniprot No.

Target Background

Function
This antibody binds to double-stranded RNA.
Database Links

Q&A

What is HLA-DRB3 and how does it function in the immune system?

HLA-DRB3 is a beta chain component of MHC class II molecules, encoded by genes located on the short arm of chromosome 6 (6p21.3). The class II molecules are heterodimers consisting of an alpha (DRA) and a beta (DRB) chain. HLA-DRB3 is expressed on the surface of antigen-presenting cells (APCs) including B cells, macrophages, and dendritic cells . Its primary function involves adaptive immune responses by presenting peptide antigens to CD4+ T cells .

Unlike the universal expression of some HLA genes, the HLA-DRB3 gene is only present in a subset of individuals, creating significant implications for immunological compatibility in clinical settings . This limited distribution contributes to its frequent mismatching in organ transplantation scenarios, where patients lacking the gene may develop antibodies when exposed to donor tissue expressing DRB3 .

What experimental techniques are most reliable for detecting HLA-DRB3 antibodies?

Multiple methodological approaches exist for detecting HLA-DRB3 antibodies, with solid phase assays being particularly effective in clinical research settings. The following techniques are most commonly employed:

ApplicationTechniqueRecommended DilutionNotes
Western Blot (WB)Protein immunoblotting1:5000-1:50000Effective for Daudi, Raji, and Ramos cell lines
Immunofluorescence (IF)Fluorescent antibody staining1:200-1:800Optimal for Raji cells
ELISAEnzyme-linked immunosorbent assayVariableSample-dependent optimization required
Solid Phase AssaysBead-based multiplex technologyAs per manufacturerUsed in clinical screening, detects multiple antibody reactivity patterns

It is critical to note that researchers should titrate these antibodies in each testing system to obtain optimal results, as reactivity is often sample-dependent . For transplantation research specifically, solid phase assays have demonstrated the capacity to identify DRB3 antibodies in approximately 7% of screened patients, while also revealing multiple antibody reactivity patterns that indicate DRB3 harbors multiple epitopes .

How do researchers characterize the molecular properties of HLA-DRB3 antibodies?

Characterization of HLA-DRB3 antibodies requires multiple parameters to ensure experimental validity:

PropertySpecification for HLA-DRB3 AntibodyApplication Relevance
Host/IsotypeRabbit/IgG (for antibody 16789-1-AP)Determines secondary antibody selection
ClassPolyclonalAffects epitope recognition breadth
ReactivityHuman-specificCritical for experimental design
Molecular WeightCalculated: 30 kDa (266 aa); Observed: 28-30 kDaImportant for band identification
ImmunogenHLA-DRB3 fusion proteinDetermines specificity
Purification MethodAntigen affinity purificationAffects antibody purity
Storage RequirementsPBS with 0.02% sodium azide and 50% glycerol pH 7.3; -20°CCritical for maintaining reactivity

When designing experiments, researchers must consider that aliquoting is unnecessary for -20°C storage, and the antibody remains stable for one year after shipment. Additionally, 20μl sizes contain 0.1% BSA, which may affect certain applications .

What is the relationship between HLA-DRB3 alleles and transplant rejection risk?

The relationship between HLA-DRB3 alleles and transplant rejection risk is multifaceted, with research indicating several key factors that influence immunogenicity:

  • Prevalence of antibody development: Approximately 7% of kidney transplant patients develop HLA-DRB3 antibodies when screened with solid phase assays .

  • Epitope diversity: DRB3 harbors multiple epitopes, resulting in diverse antibody reactivity patterns that complicate cross-matching procedures .

  • Associated DRB1 allele groups: Studies have demonstrated different frequencies of HLA-DRB1 allele groups in donors who triggered antibody formation compared to control groups .

  • Expression level variation: The immunogenicity of certain DRB1 alleles (e.g., HLA-DRB1*11) appears linked to altered expression levels, suggesting a threshold effect in antibody formation .

  • Allele-specific immunogenicity: Different HLA-DRB3 alleles (particularly the HLA-DRB3*01 group) demonstrate varying immunogenicity independent of expression differences .

These findings have significant implications for transplantation protocols, suggesting that both the presence of specific alleles and their expression levels contribute to antibody formation risk. Researchers investigating transplant rejection should consider both molecular typing and quantitative expression analysis when evaluating immunological compatibility .

How do HLA-DRB3 alleles influence autoimmune disease susceptibility?

HLA-DRB3 alleles demonstrate complex relationships with autoimmune disease susceptibility, particularly in type 1 diabetes. Next-generation sequencing studies have revealed that these alleles can significantly modify the risk conferred by HLA-DRB1 haplotypes:

  • DRB301:01:02 and DRB302:02:01 substantially affect the association between type 1 diabetes and DRB1*03:01:01 .

  • These same DRB3 alleles show divergent autoantibody associations:

    • Positive association with GAD autoantibodies (GADA)

    • Negative association with insulin autoantibodies (IAA)

    • Negative association with IA-2 antigen (IA-2A)

    • Negative association with zinc transporter 8 antibodies (ZnT8WA)

  • The protective effect of DRB1*13:01:01 against type 1 diabetes is differentially modified by DRB3 alleles:

    • DRB3*01:01:02 increases disease risk

    • DRB3*02:02:01 maintains the protective association

The research indicates that DRB302:02 allele not only serves as a marker of high-risk DRB1-DRB3 haplotypes but also independently increases the risk for DRB103:01 haplotypes . These findings underscore the importance of comprehensive HLA typing using next-generation sequencing for accurately assessing autoimmune disease risk and for selecting participants in prevention or intervention trials .

What is the dose-dependent impact of HLA-DRB3*01:01 on immune responses?

Research has demonstrated that HLA-DRB3*01:01 exhibits a clear dose-dependent effect on immune responses, particularly in the context of Human Platelet Antigen-1a (HPA-1a) immunization. This phenomenon has significant implications for both theoretical immunology and clinical applications:

  • Antibody level correlation: HLA-DRB3*01:01 shows a dose-dependent impact on HPA-1a antibody levels in HPA-1a–immunized women giving birth to HPA-1a–positive children .

  • Clinical outcomes: The dose of HLA-DRB3*01:01 inversely affects neonatal platelet counts in HPA-1a–positive children born to HPA-1a–immunized women, with higher doses correlating with lower platelet counts .

  • Mechanistic basis: Crystallographic studies have demonstrated that the peptide from human platelet integrin β3 glycoprotein, which harbors leucine at residue 33 (the HPA-1a epitope), fits perfectly into the cleft of the HLA molecule encoded by HLA-DRA/DRB3*01:01 .

These findings align with the broader understanding that antibody development against specific antigens requires help from antigen-specific T cells. The dose effect observed suggests that homozygosity for HLA-DRB3*01:01 leads to more efficient antigen presentation and subsequent T-cell help, resulting in heightened antibody responses . This knowledge has crucial implications for predicting immunization outcomes and understanding variable clinical presentations in immunohematology.

How do researchers differentiate between pathogenic and non-pathogenic HLA-DRB3 antibodies?

Differentiating between pathogenic and non-pathogenic HLA-DRB3 antibodies represents a significant challenge in transplantation immunology. Research-based approaches to this distinction include:

  • Epitope specificity analysis: Multiple antibody reactivity patterns observed in solid phase assays indicate that HLA-DRB3 harbors multiple epitopes, which may differ in their pathogenic potential .

  • Correlation with clinical outcomes: Retrospective analysis of transplant outcomes in patients with specific antibody patterns helps identify which epitope specificities correlate with rejection events .

  • Expression level consideration: Research indicates that the immunogenicity of certain HLA alleles is linked to their expression levels, suggesting that antibodies against highly-expressed epitopes may have greater pathogenic potential .

  • Allele-specific immunogenicity: Studies reveal that different HLA-DRB3 alleles (e.g., HLA-DRB3*01 group) vary in their immunogenicity independently of expression differences, pointing to structural features that may influence pathogenicity .

  • Molecular typing correlation: By tracing back the induction of antibodies to the molecular HLA typing of the immunogenic event, researchers can identify patterns that predict clinically significant responses .

These differentiation strategies have significant implications for risk assessment in transplantation medicine, potentially allowing for more nuanced cross-matching procedures that distinguish between harmful and innocuous antibody responses.

What experimental designs best elucidate the interaction between HLA-DRB3 and HLA-DRB1 in disease risk modulation?

The complex interaction between HLA-DRB3 and HLA-DRB1 in modulating disease risk requires sophisticated experimental designs. Based on current research, the following approaches are recommended:

  • Next-generation sequencing (NGS) of all DRB alleles: This approach provides comprehensive typing that reveals how DRB3 alleles modify the risk conferred by DRB1 for autoimmune conditions .

  • Case-control studies with large cohorts: These studies should include:

    • Patients with confirmed autoimmune disease (e.g., type 1 diabetes)

    • Age-matched control subjects

    • Complete HLA typing

    • Autoantibody profiling

  • Haplotype risk scoring: Research has developed an H-score system to quantify risk associations:

    • DRB103:01:01 (H-score modified by DRB301:01:02 and DRB3*02:02:01)

    • DRB1*07:01:01 (H-score −9, modified by DRB4 alleles)

    • DRB1*13:01:01 (H-score −7, modified by DRB3 alleles)

  • Autoantibody stratification: Dividing subjects based on autoantibody profiles (e.g., GADA, IAA, IA-2A, ZnT8RA, ZnT8WA, ZnT8QA) reveals how specific HLA combinations affect immune response patterns .

  • Expression quantification studies: These investigations help determine whether risk modification occurs through altered expression levels or through structural differences in the resulting proteins .

The complexity of these interactions is illustrated by findings that some DRB3/DRB4 alleles show opposite risks when analyzed individually versus when present in specific DRB1 haplotypes. For example, DRB107:01:01 is modified by both DRB401:01:01 (H-score −3) and DRB401:03:01 (H-score 13); despite these opposite individual risks, the combined effect on the DRB107:01:01 haplotype is negative .

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