Mafa Antibody
Description
Overview of Mafa Antibody
The Mafa antibody targets the MafA protein, a member of the Maf family of transcription factors. MafA is enriched in pancreatic islet beta cells and regulates insulin gene transcription, glucose responsiveness, and beta-cell differentiation . It is also expressed in alpha cells under specific conditions . The antibody is employed in immunological assays to study MafA expression in diabetes, autoimmunity, and pancreatic development.
Antibody Types and Specificity
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Polyclonal (e.g., Abcam ab26405): Reacts with human samples, validated for Western blot (WB), immunofluorescence (IF), and immunohistochemistry (IHC). Specificity confirmed by absence of cross-reactivity with MafB .
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Recombinant Monoclonal (e.g., Bethyl BLR067G): Targets a peptide spanning residues 125–175 of human MafA, ensuring high specificity .
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Cross-reactivity: Some antibodies (e.g., Abcam ab26405) exhibit reactivity with human, mouse, and rat samples .
Predicted vs. Observed Band Sizes
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Abcam ab26405: Predicted band size = 36 kDa (reducing conditions); observed size matches this in Western blot .
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Bethyl BLR067G: Specificity confirmed via peptide immunization and Western blot validation .
Applications
Role in Autoimmunity
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Mafa Deficiency: Linked to islet inflammation, pro-inflammatory cytokine upregulation, and autoimmune T-cell activation .
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Immune Crosstalk: MafA regulates T-cell activation and suppresses interferon responses, preventing adaptive autoimmunity .
Pancreatic Expression
Product Specs
Constituents: 50% Glycerol, 0.01M PBS, pH 7.4
Target Background
- Research indicates that hepatocytes can be reprogrammed into insulin-producing cells in vivo by introducing neurogenin-3, Pdx1, and MafA genes using non-viral hydrodynamics injection. This technique has shown promise in treating streptozotocin diabetes, with a reduction in fasting blood glucose levels to normal. (Pdx1 = pancreatic and duodenal homeobox 1; MafA = v-maf musculoaponeurotic fibrosarcoma oncogene family, protein A) PMID: 28100871
- Mafa has been found to enhance the ability of Pdx1 to induce beta-cell formation from Ngn3-positive endocrine precursors. Moreover, Mafa enables Pdx1 to generate beta-cells from alpha-cells, demonstrating its versatility in beta-cell development. PMID: 28223284
- MafA is essential for maintaining normal insulin levels even during embryonic development, highlighting its early role in regulating glucose homeostasis. PMID: 25912440
- Endogenous small-Maf factors have been shown to negatively regulate beta-cell function by competing with MafA for binding sites. Therefore, inhibiting small-Maf activity can potentially improve beta-cell function. PMID: 25763640
- Studies utilizing transgenic/knockout mice have confirmed that Mafa and Mafb expression is specific to insulin-secreting cells of the pancreas, emphasizing their role in beta-cell identity. PMID: 25273397
- Evidence suggests that MafA regulates the postnatal proliferation of beta-cells through prolactin signaling, contributing to beta-cell expansion after birth. PMID: 25126749
- Research has demonstrated that a reduction in Mafa activity significantly impacts islet beta-cell function under various pathological conditions, underscoring its critical role in maintaining beta-cell health. PMID: 25645923
- Findings clearly elucidate the essential role of MafA as a transcriptional regulator of islet beta-cells. Furthermore, the results highlight the coordinated actions of MafA and MafB during cell maturation. PMID: 24520122
- The activity of MAFA, MAFB, NKX6.1, and PDX1 serves as an indicator of islet beta-cell function. Loss of MAFA (and/or MAFB) represents an early sign of beta-cell inactivity. PMID: 23863625
- Under both oxidative and non-oxidative conditions, p38 MAPK directly interacts with MafA, leading to its degradation via the ubiquitin proteasomal pathway. This highlights a regulatory mechanism for controlling MafA levels. PMID: 23660596
- Researchers have explored a method for differentiating cells into insulin-producing cells by introducing three key transcription factors (Pdx1, NeuroD, and MafA) involved in pancreatic beta-cell development using protein transduction. PMID: 24292793
- Interestingly, forcing MafA expression in Ngn3(+) endocrine progenitors, outside of its normal developmental context, blocked endocrine differentiation and prevented the formation of hormone-producing cells, indicating a delicate balance in its regulation. PMID: 24183936
- MAFA has been identified as a target downregulated by miR-204. This newly discovered TXNIP-miR-204-MAFA-insulin pathway may contribute to the progression of diabetes. PMID: 23975026
- Research suggests that Onecut1 suppresses MafA gene expression through the Foxa2-binding site, further highlighting the intricate regulatory network controlling MafA expression. PMID: 23775071
- Characterization of a novel 80-88 kDa transcriptional activator enriched in beta-cell lines has revealed its ability to regulate both MafA and Pdx1 genes, providing further insights into the complex regulatory network within beta-cells. PMID: 23269676
- MicroRNA-30d has been found to induce insulin transcription factor MafA and insulin production by targeting mitogen-activated protein 4 kinase 4 (MAP4K4) in pancreatic beta-cells. This demonstrates the involvement of microRNAs in regulating beta-cell function. PMID: 22733810
- Combined transfection of the three transcriptional factors, PDX-1, NeuroD1, and MafA, has been shown to induce differentiation of bone marrow mesenchymal stem cells into insulin-producing cells, opening up possibilities for regenerative medicine approaches. PMID: 22761608
- Results indicate that Pdx1 and MafA play a crucial role in directing DE progenitors towards insulin-producing cells, highlighting their role in beta-cell lineage specification. PMID: 22563503
- Research has investigated the mechanism of transdifferentiation of pancreatic exocrine cells into beta (beta) cells in vivo mediated by MafA, providing valuable insights into the plasticity of pancreatic cells. PMID: 22150363
- When injected in utero into living mouse embryos, TAT-MafA significantly up-regulates target genes and induces enhanced insulin production, accompanied by structural changes consistent with accelerated islet maturation. PMID: 21857924
- PA28gamma stimulates MAFA degradation through a novel molecular mechanism distinct from the degradation of p21. This suggests a specific regulatory pathway for controlling MafA levels. PMID: 21830322
- Impaired MafA expression has been linked to beta-cell dysfunction in maturity onset diabetes of young mice. MafA mutant mice exhibited symptoms resembling human type 2 diabetes, emphasizing its importance in glucose metabolism. PMID: 21193557
- ATF2 interacts with beta-cell-enriched transcription factors, MafA, Pdx1, and beta2, and activates insulin gene transcription, demonstrating the interplay between different transcription factors in regulating insulin expression. PMID: 21278380
- Data suggests that SUMOylation, a post-translational modification of MafA, negatively regulates its transcriptional and transforming activities, providing a mechanism for fine-tuning its function. PMID: 20718938
- The bZIP transcription factor MafA has been identified as a specific marker for a subpopulation of “early c-ret” positive neurons characterized by their medium-to-large diameters, highlighting its potential role in neuronal development. PMID: 20213756
- Research provides insights into the sequential manner in which MafA regulates islet beta-cell formation and maturation in mice, shedding light on its role in beta-cell development. PMID: 20627934
- Polymorphisms in MafA have been associated with reduced expression of insulin in the thymus and susceptibility to type 1 diabetes in both NOD mice and humans, suggesting its potential role in immune regulation and diabetes pathogenesis. PMID: 20682694
- Proper regulation of Mafa expression involves interactions between various transcription factors binding to multiple conserved DNA sequences within distinct regions of the promoter, highlighting the complexity of MafA regulation. PMID: 20584984
- Increased expression of c-Jun in diabetic islets has been linked to decreased MafA expression and reduced insulin biosynthesis, a phenomenon often observed in type 2 diabetes. PMID: 20424231
- A novel relationship has been identified between the phosphoamino acid-rich transactivation and b-Zip domains of MafA in controlling its DNA-binding activity, further elucidating the mechanisms underlying MafA function. PMID: 20208071
- Utilizing conditional MafA knockout mice, researchers have demonstrated that MafA identifies the early ret-expressing sensory neurons in the dorsal root ganglia, expanding its known role in neuronal development. PMID: 20213756
- Research suggests that interactions between Ret and MafA progressively promote the differentiation and diversification of LTMs, emphasizing their crucial role in cell fate determination. PMID: 20064392
- MafA is a beta-cell-specific and glucose-regulated transcriptional activator for insulin gene expression, making it a key player in both beta-cell function and development, as well as in the pathogenesis of diabetes. PMID: 12368292
- Studies indicate that MafA is a crucial component of the RIPE3b1 activator, a protein complex essential for regulating insulin gene expression. PMID: 12917329
- MafA has been shown to play a role in regulating insulin gene expression in the liver, suggesting a broader role in glucose metabolism beyond pancreatic beta-cells. PMID: 15664997
- Research demonstrates that MafA is a key regulator of glucose-stimulated insulin secretion in vivo, highlighting its direct involvement in glucose responsiveness of beta-cells. PMID: 15923615
- FoxO1 has been shown to protect against pancreatic beta-cell failure by inducing Neurod and Mafa expression, underscoring its role in beta-cell survival and function. PMID: 16154098
- Research has elucidated the sequential binding of MafA, E47/beta2, and PDX-1 to the insulin promoter in living beta-cells, providing a detailed understanding of the temporal regulation of insulin gene expression. PMID: 16412423
- MafB may have a dual role in regulating embryonic differentiation of both beta- and alpha-cells, while MafA may predominantly regulate replication, survival, and function of beta-cells after birth, suggesting distinct roles for these related transcription factors. PMID: 16580660
- Data indicates that FoxA2, Nkx2.2, and PDX-1 regulate islet beta-cell-specific mafA expression through conserved sequences located upstream of the transcription start site, demonstrating the complex network of regulatory elements controlling MafA expression. PMID: 16847327
- High glucose-mediated MafA expression requires flux through the hexosamine biosynthetic pathway and O-linked glycosylation of an unknown protein(s) by UDP-N-acetylglucosaminyl transferase, highlighting a novel glucose-sensing mechanism. PMID: 17142462
- Ripe3b1 has been shown to induce islet cell differentiation in hepatic progenitor cells, demonstrating its potential role in reprogramming cells into insulin-producing cells. PMID: 17239820
- Research suggests a potential role for mafA in impaired metabolic responses or inflammatory reactions, highlighting its broader implications in disease pathogenesis. PMID: 17346669
- MafA plays a critical role in islet beta-cell function, emphasizing its significance in maintaining proper glucose homeostasis. PMID: 17636040
- MafA is constitutively phosphorylated by GSK3, suggesting a new glucose-sensing signaling pathway in islet beta cells that regulates insulin gene expression through MafA protein stability. PMID: 17682063
- MafA-dependent activation of insulin II gene promoters was inhibited in the presence of Smad2/Smad4 or Smad3/Smad4 and a constitutively active TGF-beta type I receptor, indicating that TGF-beta signaling can negatively regulate insulin expression. PMID: 17927952
- The significance of large Maf proteins, particularly MafB, has been recognized in regulating Pdx1 expression in beta cells during pancreatic development. PMID: 18522939
- The mobility of MafA S65A was significantly affected upon SDS-PAGE, while the S65E and S65D mutants were less influenced, suggesting a role for phosphorylation in regulating MafA protein stability. PMID: 19004825
- Research indicates that SUMO modification of MafA modulates gene transcription and, consequently, beta-cell function, suggesting a role for SUMOylation in fine-tuning MafA activity. PMID: 19029092
- p38 MAPK has been identified as a major regulator of MafA protein stability under oxidative stress, highlighting its importance in protecting beta-cells from oxidative damage. PMID: 19407223
Q&A
What is MAFA and why is it significant in research?
MAFA is a transcription factor critical for the development, maintenance, and physiological function of insulin-producing pancreatic β-cells. It regulates β-cell transcription factors (such as PDX1) and the insulin gene, making it an important target in diabetes research . The MAFA gene is sensitive to physiological glucose levels, and targeted deletion of the MAFA gene in mice leads to a loss of β-cell identity and function . Its significance lies in its potential as a target for translational and clinical research studies in diabetes, as ectopic expression of MAFA can induce insulin production by pancreatic α-cells, while conditional overexpression can promote transdifferentiation of α-cells into insulin-producing β-cells .
What species reactivity should I consider when selecting a MAFA antibody?
Available MAFA antibodies vary in their species reactivity profiles:
| Antibody | Human | Mouse | Rat | Other Species |
|---|---|---|---|---|
| Boster Bio RP1066 | Yes | No | Yes | Not tested for bovine, but may cross-react |
| Cell Signaling #79737 | Yes | Yes | Not specified | Not specified |
When selecting an antibody, always verify species reactivity against your experimental model. The Boster Bio antibody (RP1066) has been specifically tested and failed to detect MAFA in mouse samples despite showing reactivity in human and rat tissues . If working with bovine tissues, note that while cross-reactivity is possible with the RP1066 antibody, it has not been explicitly validated .
What applications are MAFA antibodies validated for?
Different MAFA antibodies are validated for specific applications:
| Antibody | Western Blot | Immunoprecipitation | Immunofluorescence | ChIP | Other |
|---|---|---|---|---|---|
| Boster Bio RP1066 | Yes (0.1-0.5μg/ml) | Not validated | Not validated | Not validated | N/A |
| Cell Signaling #79737 | Yes (1:1000) | Yes (1:200) | Yes (1:1000) | Yes (1:100) | N/A |
For optimal results, use antibodies only for validated applications. If you need to perform ChIP experiments, the Cell Signaling antibody is recommended with specific guidance: use 5 μl of antibody and 10 μg of chromatin (approximately 4 x 10^6 cells) per IP .
What controls should I include when using MAFA antibodies?
For rigorous MAFA antibody experiments, include the following controls:
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Positive controls: Use well-characterized tissue/cell lysates known to express MAFA. Validated positive controls for Western blot include human HEK293, K562, and 22RV1 whole cell lysates, as well as rat PC-12 whole cell lysates .
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Negative controls: Include samples from MAFA knockout models or tissues known not to express MAFA.
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Loading controls: For Western blot quantification, include housekeeping proteins (β-actin, GAPDH) to normalize expression levels.
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Blocking peptide controls: If available, use the immunizing peptide to confirm antibody specificity.
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Isotype controls: Include matched isotype antibodies (e.g., rabbit IgG for rabbit-derived MAFA antibodies) to control for non-specific binding.
These controls help validate antibody specificity and ensure experimental rigor in your MAFA studies.
How should I optimize Western blot conditions for MAFA detection?
For optimal Western blot detection of MAFA, follow these guidelines:
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Sample preparation: Use 50μg of protein per lane under reducing conditions .
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Gel electrophoresis: Run samples on a 5-20% SDS-PAGE gel at 70V (stacking gel) followed by 90V (resolving gel) for 2-3 hours .
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Transfer conditions: Transfer proteins to a nitrocellulose membrane at 150mA for 50-90 minutes .
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Blocking: Block the membrane with 5% non-fat milk in TBS for 1.5 hours at room temperature .
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Primary antibody incubation: Incubate with anti-MAFA antibody at the recommended dilution (0.5 μg/mL for Boster Bio RP1066 or 1:1000 for Cell Signaling #79737) overnight at 4°C .
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Washing: Wash the membrane with TBS-0.1% Tween three times, 5 minutes each .
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Secondary antibody: Probe with a goat anti-rabbit IgG-HRP secondary antibody at 1:5000 dilution for 1.5 hours at room temperature .
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Detection: Develop using an enhanced chemiluminescent detection kit .
Note that the expected molecular weight for MAFA varies between antibodies: approximately 37kDa for Boster Bio RP1066 and 50kDa for Cell Signaling #79737 .
How can I use MAFA antibodies to study pancreatic β-cell function?
MAFA antibodies can be employed in multiple experimental approaches to study β-cell function:
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Expression analysis: Use Western blot to quantify MAFA protein levels in response to experimental conditions such as varying glucose concentrations, as the MAFA gene is sensitive to physiological glucose levels .
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Chromatin immunoprecipitation (ChIP): Employ ChIP using MAFA antibodies to identify genomic targets regulated by MAFA, including β-cell transcription factors and the insulin gene .
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Co-immunoprecipitation (Co-IP): Investigate protein-protein interactions between MAFA and other transcription factors or regulatory proteins in β-cell function.
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Immunofluorescence: Examine subcellular localization of MAFA in pancreatic tissue sections or cultured β-cells under different conditions.
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Cell lineage tracing: Combine MAFA antibodies with other β-cell markers to study transdifferentiation events, as MAFA overexpression has been shown to promote transdifferentiation of α-cells into insulin-producing β-cells .
These approaches can provide insights into the molecular mechanisms by which MAFA regulates β-cell identity, insulin production, and response to glucose.
What considerations are important when using MAFA antibodies in studies of diabetes models?
When applying MAFA antibodies in diabetes research models, consider:
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Model selection: Different diabetes models (type 1, type 2, gestational) may show varied MAFA expression patterns. Consider whether your model reflects the pathophysiological conditions you aim to study.
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Species-specific variations: Ensure your chosen antibody reacts with the species of your model. For instance, RP1066 works with human and rat samples but not mouse samples .
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Temporal dynamics: MAFA expression changes during disease progression. Design experiments to capture relevant timepoints in disease development.
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Functional validation: Complement antibody-based detection with functional assays, as MAFA is critically involved in regulating insulin production.
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Islet heterogeneity: Consider that pancreatic islets contain multiple cell types; use co-staining approaches to distinguish β-cells from other islet cells when using immunohistochemistry or immunofluorescence.
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Quantification methods: Develop robust quantification strategies for MAFA expression across different experimental conditions, considering both protein levels and transcriptional activity.
These considerations will enhance the translational relevance of your diabetes research when using MAFA antibodies.
Why might I see unexpected molecular weight bands when using MAFA antibodies?
Multiple or unexpected bands in MAFA Western blots may result from:
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Post-translational modifications: MAFA undergoes phosphorylation and other modifications that can alter its electrophoretic mobility.
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Splice variants: Alternative splicing may produce different MAFA isoforms.
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Degradation products: Sample preparation conditions may cause protein degradation, resulting in lower molecular weight fragments.
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Cross-reactivity: Antibodies may recognize other MAF family members (MAFB, c-MAF) due to sequence homology.
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Non-specific binding: Insufficient blocking or high antibody concentrations can lead to non-specific bands.
To address these issues:
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Compare your observed band pattern with the expected molecular weight (37kDa for Boster Bio RP1066, 50kDa for Cell Signaling #79737)
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Include positive controls with known MAFA expression
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Optimize blocking conditions and antibody dilutions
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Consider peptide competition assays to identify specific versus non-specific bands
How can I enhance antibody stability and performance in long-term studies?
For optimal antibody stability and performance:
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Storage conditions: Store lyophilized antibodies at -20°C. After reconstitution, store at 4°C for up to one month or aliquot and store at -20°C for up to six months .
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Avoid freeze-thaw cycles: Repeated freeze-thaw cycles can degrade antibody activity. Prepare small aliquots for single use .
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Consider antibody engineering approaches: Recent research suggests machine learning methods can help predict antibody thermostability . While primarily applicable to therapeutic antibodies, these principles may inform research antibody handling.
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Buffer optimization: If needed, add stabilizing proteins (BSA) or preservatives to maintain antibody activity.
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Quality control: Periodically validate antibody performance against positive controls to ensure consistent results over time.
Proper antibody handling is essential for reproducible results in longitudinal studies of MAFA expression and function.
How might computational methods improve MAFA antibody development and application?
Recent advances in computational biology offer opportunities for MAFA antibody research:
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Predicting antibody stability: Machine learning approaches, including pre-trained language models and convolutional neural networks with Rosetta energetic features, can predict antibody thermostability with moderate success (average Spearman correlation coefficient of 0.4) .
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Optimizing antibody sequences: Computational deep mutational scanning can identify potential mutations that might improve antibody performance. For example, studies have demonstrated the ability to predict thermostable mutations with 25% success rate (correct residue positions and amino acid residues) and 90% success in identifying relevant residue positions .
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Structure-based antibody design: Using structural information about MAFA protein and epitopes to design more specific antibodies with enhanced binding properties.
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Cross-reactivity prediction: Computational tools may help predict cross-reactivity with other species or proteins, potentially extending the utility of existing MAFA antibodies.
These computational approaches may eventually lead to improved antibody reagents for MAFA research, though they are primarily being developed for therapeutic antibodies rather than research reagents currently .
