DNM2 Antibody, Biotin conjugated

What is the molecular structure and function of Dynamin 2 (DNM2)?

Dynamin 2 is a GTPase protein encoded by the DNM2 gene with a canonical structure of 870 amino acid residues and a molecular mass of approximately 98.1 kDa in humans . It functions primarily in endocytosis, particularly in clathrin-mediated vesicle formation and membrane fission processes . The protein contains multiple domains including a GTPase domain, middle domain, pleckstrin homology (PH) domain, GTPase effector domain (GED), and a proline-rich domain (PRD). Alternative splicing yields five distinct isoforms with tissue-specific expression patterns, allowing for specialized functions in different cellular environments . DNM2 localizes to membranes, cytoplasmic vesicles, and the cytoplasm, where it forms oligomeric structures that facilitate membrane constriction during vesicle budding . Its GTPase activity provides the mechanical force necessary for membrane scission during the final stages of endocytosis.

What are the critical differences between polyclonal and monoclonal antibodies targeting DNM2?

Polyclonal DNM2 antibodies, such as the biotin-conjugated rabbit polyclonal antibody targeting amino acids 640-1119, recognize multiple epitopes across the target region, providing robust detection but potential cross-reactivity . These antibodies are generated by immunizing animals (typically rabbits) with recombinant DNM2 protein fragments, resulting in a heterogeneous mixture of antibodies with varying affinities and epitope recognition profiles. In contrast, monoclonal antibodies like clone 3F5F3 (targeting aa 520-744) or clone 6C9 (targeting aa 611-710) recognize single epitopes with high specificity . This specificity offers advantages for discriminating between DNM2 isoforms or detecting specific post-translational modifications but may be vulnerable to epitope masking in complex samples. Polyclonals demonstrate greater tolerance to protein denaturation, making them suitable for Western blotting and fixed-tissue IHC, while monoclonals typically offer superior reproducibility between lots and experiments. For studies requiring distinction between highly homologous Dynamin family members (DNM1, DNM2, DNM3), monoclonal antibodies targeting unique regions are preferable to avoid cross-reactivity, although well-characterized polyclonals with demonstrated specificity can also be suitable.

How can DNM2 antibodies be utilized to study the role of dynamins in neurodegenerative diseases?

DNM2 antibodies, including biotin-conjugated variants, serve as critical tools for investigating dynamin's role in neurodegenerative pathologies through multiple methodological approaches. In Charcot-Marie-Tooth (CMT) disease research, where DNM2 mutations (particularly those designated as CMTDI1, CMTDIB, and CMT2M) contribute to pathogenesis, these antibodies enable immunohistochemical analysis of patient-derived neuronal cultures to visualize abnormal DNM2 localization patterns . Researchers can employ proximity ligation assays (PLA) using biotinylated DNM2 antibodies combined with antibodies against interacting proteins to quantify altered protein-protein interactions in disease models. For mechanistic studies, pulse-chase experiments using temporally controlled DNM2 labeling help track defective vesicle trafficking dynamics in real-time. Western blot analysis with DNM2 antibodies of brain tissue fractions from Alzheimer's and Parkinson's disease models can reveal alterations in DNM2 expression, oligomerization states, or post-translational modifications (particularly phosphorylation patterns) . Comparative immunoprecipitation studies between wild-type and disease models identify disease-specific binding partners, providing insights into pathological mechanisms. When combined with super-resolution microscopy techniques such as STORM or PALM, biotinylated DNM2 antibodies with streptavidin-fluorophore conjugates enable nanometer-scale visualization of dynamin distribution at synaptic terminals and other neuronal compartments, revealing subtle structural abnormalities preceding symptomatic onset.

What are the methodological considerations for using biotinylated DNM2 antibodies in live-cell imaging?

When implementing biotinylated DNM2 antibodies for live-cell imaging, researchers must address several methodological challenges. First, cell membrane permeabilization requires careful optimization, as traditional detergent-based methods (0.1% Triton X-100) can disrupt membrane dynamics that DNM2 naturally regulates . Instead, gentle permeabilization with streptolysin O (25-50 ng/mL) or digitonin (10-20 μg/mL) is recommended to maintain cellular integrity while allowing antibody entry. Second, the detection system must be optimized—using streptavidin conjugated to small, bright fluorophores (Quantum dots or Alexa Fluor 647) provides superior signal-to-noise ratio compared to larger fluorescent proteins. When performing dual-labeling experiments to track DNM2 alongside interacting proteins, sequential labeling with appropriate blocking steps (using 5% bovine serum albumin with 0.1% fish gelatin) prevents cross-reactivity and false colocalization signals . Temperature control is critical, as DNM2-mediated endocytosis is temperature-sensitive; imaging should be conducted at physiological temperature (37°C) with a heated stage apparatus rather than room temperature. Time-resolved imaging protocols should incorporate photobleaching correction algorithms to compensate for signal loss during extended imaging sessions. Validation controls must include competitive binding with excess unlabeled antibody, dynamin inhibitors (e.g., Dynasore at 80 μM), and parallel imaging in DNM2-knockdown cells to confirm specificity of the observed signals.

How can biotinylated DNM2 antibodies be employed in studying cellular mechanotransduction pathways?

Biotinylated DNM2 antibodies offer sophisticated approaches for investigating dynamin's role in mechanotransduction—the cellular processes converting mechanical stimuli into biochemical signals. When studying focal adhesion dynamics, researchers can utilize these antibodies in combination with mechanical stimulation platforms (such as stretchable substrates or magnetic twisting cytometry) to track DNM2 recruitment to mechanosensitive structures . For quantitative analysis, researchers should implement force application protocols with defined parameters (typically 10-20% substrate strain at 0.5-1 Hz for physiological relevance) while simultaneously monitoring DNM2 localization and conformational changes using fluorescence resonance energy transfer (FRET) with the biotinylated antibody serving as the acceptor fluorophore. In microfluidic shear stress models simulating vascular environments, the combination of biotinylated DNM2 antibodies with quantum dot labeling enables single-molecule tracking of DNM2 dynamics in response to fluid forces (typically 10-40 dyne/cm² to mimic physiological arterial flow). For advanced studies, AFM-based force spectroscopy combined with super-resolution microscopy utilizing biotinylated DNM2 antibodies can correlate local membrane tension changes with dynamin recruitment and activation. Key controls should include cytoskeletal disruption experiments (using cytochalasin D at 1 μM or nocodazole at 10 μM) to distinguish direct mechanical sensing by DNM2 from cytoskeleton-mediated effects. Data analysis should incorporate computational approaches that correlate spatio-temporal DNM2 dynamics with force vector maps to establish causative relationships between mechanical stimuli and dynamin activation.

What is the optimal protocol for using biotinylated DNM2 antibodies in multi-color immunofluorescence studies?

The optimal protocol for multi-color immunofluorescence using biotinylated DNM2 antibodies requires careful consideration of several parameters to achieve specific labeling with minimal background. Begin with appropriate sample preparation: for cultured cells, fix with 4% paraformaldehyde for 15 minutes at room temperature followed by permeabilization with 0.2% Triton X-100 for 10 minutes . For tissue sections, use 10 μm thickness with antigen retrieval in citrate buffer (pH 6.0) at 95°C for 20 minutes. Block samples thoroughly with 5% normal serum from a species different from all primary antibodies plus 1% BSA for 60 minutes at room temperature. When incorporating the biotinylated DNM2 antibody, use it at 1:200-1:500 dilution (optimized through titration) and always include an avidin/biotin blocking step (15 minutes each) before application to eliminate endogenous biotin interference . For multi-color detection, apply the detection reagents in a specific order: (1) detect non-biotinylated primary antibodies with directly labeled secondary antibodies, (2) apply streptavidin conjugate (Alexa Fluor 488, 555, or 647) at 1:1000 dilution to visualize the biotinylated DNM2 antibody. Include appropriate controls: (1) omission of primary antibody, (2) isotype control, (3) blocking peptide competition, and (4) counter-staining with another DNM2 antibody recognizing a different epitope to confirm specificity. For optimal resolution, image using a confocal microscope with appropriate bandwidth settings to minimize spectral overlap, and perform acquisition with sequential scanning rather than simultaneous detection to prevent crosstalk between channels.

What are the essential considerations for quantitative analysis of DNM2 expression using biotinylated antibodies in ELISA?

Quantitative analysis of DNM2 expression using biotinylated antibodies in ELISA requires meticulous attention to methodological details. First, establish a calibration curve using recombinant DNM2 protein (preferably covering the range of 0.1-100 ng/mL) with at least 7 concentration points and triplicate measurements for each . For sandwich ELISA, coat high-binding microplates with a capture antibody recognizing a different DNM2 epitope than the biotinylated detection antibody to prevent epitope competition. Standard coating conditions include 1-2 μg/mL antibody in carbonate buffer (pH 9.6) overnight at 4°C. Block residual binding sites with 2% BSA in PBS-T (PBS with 0.05% Tween-20) for 2 hours at room temperature . When preparing cell lysates for analysis, standardize the protocol using RIPA buffer containing protease inhibitor cocktail, followed by protein quantification via BCA assay to ensure equal loading across samples (typically 50-100 μg total protein per well). For detection, the optimal concentration of biotinylated DNM2 antibody (typically 0.5-2 μg/mL) should be determined through checkerboard titration against various sample concentrations. Use streptavidin-HRP at 1:5000-1:10000 dilution with TMB substrate development for 15-30 minutes before stopping with 2N H₂SO₄. Data analysis must include: (1) blank subtraction, (2) four-parameter logistic regression for standard curve fitting, (3) coefficient of variation calculation (<15% acceptable), and (4) spike recovery tests (80-120% recovery indicates acceptable matrix effects). Include positive control samples with known DNM2 concentrations and negative controls using lysates from DNM2-knockdown cells.

How should researchers optimize biotinylated DNM2 antibody concentration for chromatin immunoprecipitation sequencing (ChIP-seq)?

Optimizing biotinylated DNM2 antibody concentration for ChIP-seq requires a systematic approach tailored to this non-canonical application, as DNM2 is not typically characterized as a DNA-binding protein. When investigating potential chromatin interactions or using DNM2 as part of a larger complex, researchers should first validate the antibody's specificity in this context through preliminary ChIP-qPCR experiments using a titration range (2-10 μg of antibody per 25-30 μg of chromatin) . Cross-linking conditions must be carefully optimized: for protein-protein interactions within DNM2-containing complexes, use a dual cross-linking approach with 1.5 mM ethylene glycol bis(succinimidyl succinate) (EGS) for 30 minutes followed by 1% formaldehyde for 10 minutes at room temperature. Sonication parameters should be adjusted to generate DNA fragments of 200-300 bp (typically 10-15 cycles of 30 seconds on/30 seconds off at medium power using a Bioruptor or similar device). For immunoprecipitation, use streptavidin-conjugated magnetic beads pre-blocked with 1 mg/mL BSA and 0.5 mg/mL sheared salmon sperm DNA. Include additional controls beyond the standard IgG control: (1) ChIP with an antibody against a known DNM2-interacting transcription factor, (2) ChIP after DNM2 knockdown, and (3) ChIP with a non-biotinylated DNM2 antibody followed by protein A/G beads to compare efficiency. For library preparation, use a minimum of 10 ng of immunoprecipitated DNA, and implement sequential ChIP (Re-ChIP) for suspected indirect DNM2-chromatin interactions. Bioinformatic analysis should employ specialized peak-calling algorithms optimized for transcription factor ChIP-seq rather than histone modification patterns, with motif enrichment analysis to identify potential DNA-binding partners.

How can researchers address non-specific binding when using biotinylated DNM2 antibodies in tissue with high endogenous biotin?

Non-specific binding is a significant challenge when using biotinylated antibodies in biotin-rich tissues such as liver, kidney, and brain. To overcome this limitation with biotinylated DNM2 antibodies, researchers should implement a comprehensive blocking strategy beginning with avidin-biotin blocking kit treatment prior to antibody incubation . The protocol should include sequential application of unconjugated avidin (0.1 mg/mL for 15 minutes) followed by excess biotin (0.5 mg/mL for 15 minutes) to saturate endogenous biotin and any remaining avidin binding sites. For tissues known to have extremely high biotin content, researchers should consider alternative detection systems like tyramide signal amplification, which provides similar sensitivity without biotin dependency. When biotinylated antibodies must be used, pre-treatment of tissue sections with 0.3% hydrogen peroxide in methanol for 30 minutes helps reduce endogenous peroxidase activity that can contribute to background in HRP-based detection systems . Sample preparation should include prolonged washing steps (at least 3 washes of 10 minutes each) after both primary antibody and streptavidin-conjugate incubations. Control experiments are essential for accurate interpretation: parallel staining with non-biotinylated DNM2 antibody of the same clone using standard secondary detection methods allows direct comparison of signal patterns. Quantitative image analysis should incorporate advanced background correction algorithms such as rolling ball background subtraction with a radius greater than the largest expected DNM2-positive structure (typically 50 pixels). For publications, researchers should report the endogenous biotin blocking protocol in detail and include supplementary images of control sections stained with streptavidin-conjugate alone to demonstrate background levels.

What analytical approaches can differentiate between specific DNM2 isoforms when using antibodies targeting shared epitopes?

Differentiating between DNM2 isoforms requires sophisticated analytical approaches when using antibodies that target epitopes shared across multiple splice variants. The five identified DNM2 isoforms differ primarily in the middle and PH domains due to alternative splicing of exons 10, 13, and 14 . When working with biotinylated antibodies targeting the shared region (amino acids 640-1119), researchers can employ several complementary techniques for isoform differentiation. First, high-resolution SDS-PAGE using 6% acrylamide gels with extended run times (6-8 hours at constant 80V) can separate isoforms with small molecular weight differences (2-5 kDa). Two-dimensional electrophoresis combining isoelectric focusing (pH gradient 5-8) with SDS-PAGE provides superior separation based on both charge and size differences between isoforms. For proteomic verification, immunoprecipitation with the biotinylated DNM2 antibody followed by mass spectrometry analysis using selected reaction monitoring (SRM) can identify isoform-specific peptide fragments with mass differences as small as 1-2 Da. RNA-based correlation analysis provides valuable complementary data—researchers should perform parallel RT-qPCR using isoform-specific primers to correlate protein detection patterns with mRNA expression. Computational image analysis of immunofluorescence data can reveal isoform-specific subcellular localization patterns; statistical clustering of intensity profiles across multiple cellular compartments (using k-means or hierarchical clustering algorithms) often reveals distinct spatial signatures for different isoforms despite using a shared-epitope antibody. For definitive isoform assignment, researchers should validate findings with knockdown experiments using isoform-specific siRNAs, followed by densitometric analysis of Western blots to quantify the relative depletion of specific bands.

How can researchers validate the specificity of their experimental findings when using biotinylated DNM2 antibodies?

Comprehensive validation of experimental findings using biotinylated DNM2 antibodies requires a multi-level approach to confirm specificity. At the antibody validation level, researchers should perform Western blot analysis against recombinant DNM2 protein, wild-type cell lysates, and DNM2-knockdown samples, looking for appropriate molecular weight bands (approximately 98 kDa) that disappear in knockdown samples . Peptide competition assays, where pre-incubation of the antibody with excess immunizing peptide blocks specific binding, provide additional confirmation. For rigorous cross-reactivity assessment, test the antibody against purified DNM1 and DNM3 proteins, which share significant sequence homology with DNM2. At the cellular level, implement RNA interference using at least two independent siRNA sequences targeting DNM2, then compare immunostaining patterns before and after knockdown—specific signals should decrease proportionally to the knockdown efficiency as measured by RT-qPCR. For co-localization studies, validate findings using antibodies recognizing different DNM2 epitopes and quantify overlap using Pearson's or Mander's correlation coefficients (values >0.7 indicate strong co-localization). When investigating protein-protein interactions, confirm results using reciprocal immunoprecipitation and at least one orthogonal method such as proximity ligation assay or FRET. For functional studies, complement antibody-based detection with independent approaches—for example, when studying endocytosis, combine DNM2 immunostaining with transferrin uptake assays and live-cell imaging with fluorescent endocytic cargo. Statistical validation should include appropriate tests for multiple comparisons (such as ANOVA with post-hoc Tukey HSD) and calculation of effect sizes (Cohen's d values >0.8 indicate strong effects) to ensure biological significance beyond statistical significance.

What are the advantages and limitations of using biotinylated DNM2 antibodies in high-throughput screening for dynamin modulators?

How can complementary approaches be integrated with biotinylated DNM2 antibody techniques to establish comprehensive mechanistic models of dynamin function?

Establishing comprehensive mechanistic models of dynamin function requires integration of biotinylated DNM2 antibody techniques with multiple complementary methodologies. For structural insights, researchers should combine antibody-based visualization with cryo-electron microscopy of recombinant DNM2, allowing correlation between antibody epitope accessibility and conformational states . This integrated approach reveals how structural changes (particularly in the stalk and PH domains) correspond to different functional states detected by the antibody. For dynamic analyses, biotinylated antibody detection of fixed-timepoint samples should be correlated with live-cell imaging using fluorescently tagged DNM2 constructs, creating temporal maps of dynamin recruitment and dissociation during endocytosis. Quantitative mass spectrometry using stable isotope labeling (SILAC) can identify DNM2 interaction partners while parallel immunoprecipitation with biotinylated antibodies confirms these interactions in native cellular contexts. Functional studies benefit from combining antibody detection with electrophysiological measurements in neurons, correlating DNM2 distribution with synaptic vesicle cycling kinetics. For causal relationship determination, researchers should implement optogenetic tools that allow precise temporal control of DNM2 function (such as light-inducible protein dimerization systems) while monitoring effects using biotinylated antibody detection. Computational integration of these diverse datasets requires development of multi-scale models incorporating molecular dynamics simulations of DNM2 oligomerization, mesoscale models of membrane deformation, and cellular-level models of endocytic pathway regulation. Statistical approaches for data integration should employ Bayesian networks to establish causal relationships between DNM2 structural states, interaction partners, and functional outcomes. This comprehensive approach yields testable predictions about DNM2 behavior under novel conditions, creating an iterative cycle of model refinement through targeted experimental validation.