DHRS13 Antibody

What is DHRS13 and what cellular functions is it involved in?

DHRS13 (dehydrogenase/reductase SDR family member 13) is a 377 amino acid secreted protein belonging to the short-chain dehydrogenases/reductases (SDR) family. It is presumed to function as an oxidoreductase and undergoes phosphorylation, potentially by ATM or ATR, upon DNA damage. The protein exists in multiple isoforms (up to 3 have been reported) produced by alternative splicing events. With a reported mass of 40.8 kDa for the canonical protein, DHRS13 is encoded by a gene located on human chromosome 17, which contains over 1,200 genes and comprises approximately 2.5% of the human genome . While the precise cellular functions remain under investigation, its classification in the SDR family suggests roles in metabolic pathways involving oxidation-reduction reactions.

What species reactivity should be considered when selecting DHRS13 antibodies?

When selecting DHRS13 antibodies, researchers should carefully consider species reactivity based on their experimental model. Available antibodies show varying reactivity profiles. Some commercially available antibodies react only with human DHRS13 , while others demonstrate cross-reactivity with multiple species including human, mouse, rat, bovine, dog, and horse . DHRS13 gene orthologs have been reported in mouse, rat, bovine, frog, chimpanzee, and chicken . For comparative studies across species, antibodies with broader reactivity profiles may be advantageous, while species-specific antibodies may provide higher specificity for single-species research. Always validate antibody performance in your specific experimental system regardless of manufacturer claims.

What are the common applications for DHRS13 antibodies in research?

DHRS13 antibodies are employed in various research applications for detecting and studying the protein. Western blot is widely used for analyzing DHRS13 expression levels and molecular weight verification . Immunohistochemistry with paraffin-embedded sections (IHC-P) allows for visualization of DHRS13 localization in tissues at dilutions typically ranging from 1:100-500 . Immunofluorescence techniques (IF) can be performed on paraffin-embedded sections at dilutions of approximately 1:50-200 . Additionally, ELISA methods are commonly employed for quantitative detection of DHRS13 . Each application requires specific optimization of antibody concentration, incubation conditions, and detection systems to achieve optimal results while minimizing background interference.

How should researchers optimize Western blot protocols for DHRS13 detection?

For optimal Western blot detection of DHRS13, begin with sample preparation using appropriate lysis buffers containing protease and phosphatase inhibitors, especially when studying phosphorylated forms of DHRS13. Given its reported molecular weight of 40.8 kDa , use 10-12% polyacrylamide gels for optimal resolution. Recommended antibody dilutions range from 1:100-1000 , but optimization is essential for each specific antibody. When transferring proteins, PVDF membranes may provide better results than nitrocellulose for this hydrophobic protein. Include positive controls from tissues or cell lines with known DHRS13 expression. For detecting post-translational modifications like phosphorylation (which occurs after DNA damage) , consider using phospho-specific antibodies or performing phosphatase treatment controls. Blocking with 5% BSA rather than milk may reduce background when using phospho-specific antibodies. Validate antibody specificity using knockdown or knockout controls whenever possible.

What storage and handling practices maximize DHRS13 antibody performance and longevity?

To maintain optimal DHRS13 antibody performance, follow these evidence-based practices: Store antibodies according to manufacturer recommendations, typically at -20°C in small aliquots to avoid repeated freeze-thaw cycles which can degrade antibody quality . For FITC-conjugated antibodies, additional precautions are necessary - aliquot immediately upon receipt, minimize exposure to light during storage and handling, and consider using amber tubes to prevent photobleaching . Liquid formulations containing glycerol (commonly 50%) prevent freezing at -20°C and maintain antibody stability . When working with antibodies, maintain sterile conditions, use appropriate buffers (typically PBS with preservatives like Proclin-300 at 0.03%) , and keep antibodies on ice during experiments. Before each use, centrifuge antibody vials briefly to collect solution at the bottom. Monitor antibody performance over time using consistent positive controls to detect any deterioration in signal quality or specificity. Document lot numbers and maintain detailed records of performance to identify any batch-to-batch variations.

How can researchers effectively validate DHRS13 antibody specificity for their experimental system?

Comprehensive validation of DHRS13 antibody specificity requires a multi-faceted approach. Begin with genetic knockdown/knockout controls using siRNA, shRNA, or CRISPR-Cas9 targeting DHRS13, which should show corresponding reductions in antibody signal. Overexpression systems with tagged DHRS13 constructs provide positive controls and allow confirmation of antibody binding to the target protein. Peptide competition assays, where the antibody is pre-incubated with excess immunizing peptide before application to samples, should abolish specific signals if the antibody is target-specific. For polyclonal antibodies, consider antibody purification against the immunizing antigen to enhance specificity. Mass spectrometry analysis of immunoprecipitated proteins can confirm antibody target identity. When comparing multiple DHRS13 antibodies targeting different epitopes, consistent staining patterns increase confidence in specificity. Always include relevant biological controls—tissues or cell types with known DHRS13 expression levels—and compare experimental results with published literature. Document all validation steps methodically, as this information is increasingly required for publication.

What approaches can detect post-translational modifications of DHRS13, particularly phosphorylation after DNA damage?

Given that DHRS13 undergoes phosphorylation, potentially by ATM or ATR kinases following DNA damage , several specialized approaches can detect these modifications. Begin with phospho-specific antibodies that recognize specific phosphorylation sites in DHRS13, if commercially available. If not, consider custom antibody development against predicted phosphorylation sites based on consensus sequences for ATM/ATR kinases. Lambda phosphatase treatment of parallel samples can serve as controls to confirm phosphorylation-specific signals. Phos-tag™ SDS-PAGE can separate phosphorylated and non-phosphorylated forms of DHRS13 without requiring phospho-specific antibodies. For comprehensive analysis, employ mass spectrometry-based phosphoproteomics following immunoprecipitation of DHRS13. To study the dynamics of DHRS13 phosphorylation after DNA damage, treat cells with DNA-damaging agents (e.g., ionizing radiation, etoposide, or hydroxyurea) and analyze DHRS13 phosphorylation over a time course. Combine these approaches with inhibitors of ATM (KU-55933) or ATR (VE-821) to confirm the responsible kinase pathway. Co-immunoprecipitation experiments can identify interactions between DHRS13 and components of the DNA damage response machinery.

How do the different isoforms of DHRS13 impact antibody selection and experimental interpretation?

DHRS13 exists as multiple isoforms (up to 3 reported) produced by alternative splicing , necessitating careful consideration in antibody selection and data interpretation. First, determine which isoforms are expressed in your experimental system using RT-PCR with isoform-specific primers. When selecting antibodies, review the immunogen information to identify which epitope region was used and whether it is present in all isoforms. Antibodies targeting common regions will detect all isoforms, while those targeting isoform-specific regions provide selective detection. Western blots may reveal multiple bands corresponding to different isoforms; perform isoform-specific knockdowns to confirm band identity. For quantitative analyses, consider whether the detected signal represents all or specific isoforms. In immunolocalization studies, different isoforms may show distinct subcellular localizations, potentially confounding interpretation if antibodies detect multiple isoforms. When comparing results across studies, consider whether the same isoforms were detected. If studying functional differences between isoforms, isoform-specific antibodies may be necessary. For comprehensive analysis, combine detection of protein isoforms with transcript analysis to correlate expression patterns.

What strategies can address non-specific binding when using DHRS13 antibodies in immunoassays?

Non-specific binding in DHRS13 immunoassays can be systematically addressed through multiple optimization strategies. Begin by evaluating blocking solutions: compare 5% BSA, 5% non-fat dry milk, commercial blocking reagents, and species-matched normal serum to identify optimal blocking conditions. Titrate primary antibody concentration; excessive concentrations often increase background. If using a polyclonal anti-DHRS13 antibody, consider pre-absorption against tissues or cell lysates from species cross-reactivity is observed or against DHRS13-knockout samples if available. Optimize washing steps by increasing washing buffer volumes, duration, or number of washes. For Western blots, high-salt TBST (up to 500mM NaCl) can reduce non-specific ionic interactions. In immunohistochemistry and immunofluorescence, include 0.1-0.3% Triton X-100 in blocking and antibody solutions to reduce non-specific hydrophobic interactions. Secondary antibody cross-reactivity can be minimized by using highly cross-adsorbed secondary antibodies or secondary antibodies raised against the Fc region specifically. For immunofluorescence, include an autofluorescence quenching step and use Sudan Black B (0.1%) to reduce background, particularly in tissues with high lipofuscin content.

How can researchers address variability in DHRS13 antibody performance across different experimental batches?

Batch-to-batch variability in antibody performance represents a significant challenge in DHRS13 research. Implement these systematic approaches to mitigate its impact: Establish a reference standard by creating aliquots of a single high-performing antibody batch for comparison with new lots. Develop a validation protocol specific to your application that each new antibody batch must pass, including positive and negative controls. For critical experiments, purchase sufficient antibody from a single lot to complete the entire study. Document lot numbers in laboratory notebooks and publications to track performance variations. When changing lots is unavoidable, perform side-by-side comparisons using identical samples and protocols, and determine correction factors for quantitative analyses if necessary. Consider preparing a standardized positive control (e.g., lysate from DHRS13-expressing cells) in bulk, aliquoting, and using consistently across experiments to normalize results. For polyclonal antibodies, which typically show greater batch-to-batch variation than monoclonals, consider using antibody purification techniques to isolate the specific immunoglobulin fraction recognizing your epitope of interest. Maintain detailed records of performance metrics for each lot to identify patterns in variability that may inform future purchasing decisions.

What considerations are important when adapting DHRS13 antibody protocols across different tissue types?

Adapting DHRS13 antibody protocols across different tissue types requires systematic optimization to account for tissue-specific characteristics. Begin with antigen retrieval optimization: different tissues may require distinct methods (heat-induced versus protease-based) and conditions (buffer pH, duration, temperature) to effectively expose epitopes, particularly in formalin-fixed, paraffin-embedded samples. Tissues with high endogenous peroxidase activity (e.g., liver, kidney) require more thorough quenching steps when using HRP-based detection systems. Highly vascularized tissues may exhibit non-specific binding to endothelial cells; incorporate additional blocking steps using avidin/biotin blocking kits when using biotinylated detection systems. Tissues with high lipid content may require extended deparaffinization and pre-treatment with detergents to enhance antibody penetration. Background autofluorescence varies significantly between tissues; specialized quenching protocols may be necessary for each tissue type in immunofluorescence applications. The optimal antibody concentration often differs between tissues; perform titration for each new tissue type rather than applying standardized dilutions. Incubation conditions (time, temperature) may need adjustment based on tissue density and fixation level. Interpretation must consider tissue-specific expression patterns of DHRS13; include positive control tissues with known expression patterns in each experiment for comparison.

How can computational approaches and deep learning models enhance DHRS13 antibody development and selection?

Recent advances in deep learning technology offer promising approaches to enhance DHRS13 antibody development. Computational antibody design through generative deep learning models, as demonstrated in recent research , can be applied to create libraries of DHRS13-specific antibody variable regions with optimized developability attributes. These models can generate sequences with high expression potential, monomer content, and thermal stability while minimizing hydrophobicity, self-association, and non-specific binding . For researchers selecting from existing antibodies, machine learning algorithms can predict antibody performance in specific applications by analyzing amino acid sequences, structural features, and physicochemical properties. Epitope prediction tools can identify optimal antigenic determinants unique to DHRS13, particularly useful for discriminating between isoforms. Structural modeling through AlphaFold2 or RoseTTAFold can predict antibody-antigen interactions, helping researchers select antibodies likely to perform well in native protein recognition. Molecular dynamics simulations can assess binding stability and specificity across experimental conditions. For cross-reactivity analysis, sequence alignment algorithms combined with epitope conservation analysis can identify antibodies likely to work across multiple species. As these computational approaches continue to advance, they will likely reduce the need for extensive empirical testing while improving antibody performance predictability.

What role might DHRS13 play in disease mechanisms based on its cellular functions and modifications?

The involvement of DHRS13 in cellular responses to DNA damage, indicated by its phosphorylation potentially by ATM or ATR kinases , suggests potential roles in genomic stability and cancer biology. As a member of the short-chain dehydrogenases/reductases (SDR) family, DHRS13 likely catalyzes oxidation-reduction reactions involving various substrates, which could impact metabolic processes relevant to diseases like diabetes, obesity, or metabolic syndrome. The gene encoding DHRS13 maps to chromosome 17 , which is associated with multiple disorders including neurofibromatosis, dysregulated Schwann cell growth, Alexander disease, Birt-Hogg-Dube syndrome, and Canavan disease . This genomic location raises questions about potential involvement in these conditions through either direct functional roles or genetic linkage. DHRS13's status as a secreted protein suggests possible extracellular functions, perhaps in signaling pathways or extracellular matrix modifications relevant to inflammatory disorders or tissue remodeling diseases. Future research directions should include comprehensive expression profiling across normal tissues and disease states, identification of specific substrates and products of DHRS13-catalyzed reactions, characterization of protein-protein interaction networks, and evaluation of DHRS13 as a potential biomarker or therapeutic target in diseases associated with oxidative stress or DNA damage response dysregulation.

What experimental approaches can elucidate the functional significance of DHRS13 phosphorylation after DNA damage?

To understand the functional significance of DHRS13 phosphorylation following DNA damage, researchers should implement a comprehensive research strategy. Begin with site-specific mutagenesis to create phospho-mimetic (S/T→D/E) and phospho-deficient (S/T→A) DHRS13 variants at identified or predicted phosphorylation sites. Express these mutants in DHRS13-knockout cellular models to conduct phenotypic rescue experiments examining cellular responses to DNA-damaging agents. Employ proximity labeling techniques (BioID or APEX) with wild-type and phospho-mutant DHRS13 to identify phosphorylation-dependent interaction partners. Analyze potential changes in DHRS13 enzymatic activity following phosphorylation using purified recombinant protein with in vitro phosphorylation by ATM/ATR kinases. Investigate subcellular localization changes upon DNA damage using live-cell imaging with fluorescently-tagged DHRS13. Assess protein stability and turnover rates of phosphorylated versus non-phosphorylated DHRS13 through cycloheximide chase experiments. Implement CRISPR-Cas9 knock-in strategies to introduce endogenous phospho-site mutations for physiologically relevant studies. Perform transcriptomics and proteomics analyses comparing cells expressing wild-type versus phospho-mutant DHRS13 to identify downstream pathways affected by this modification. These approaches will collectively illuminate how phosphorylation modulates DHRS13 function within the cellular DNA damage response network.

What are the key considerations for developing a quantitative ELISA system for DHRS13 detection?

Developing a reliable quantitative ELISA for DHRS13 requires careful attention to multiple technical aspects. Begin by selecting antibody pairs (capture and detection) that recognize different, non-overlapping epitopes on DHRS13 to prevent competitive binding. Validate antibody specificity through Western blot and immunoprecipitation before ELISA development. For sandwich ELISA formats, determine optimal coating antibody concentration (typically 1-10 μg/ml) through checkerboard titration against varying concentrations of recombinant DHRS13. Optimize blocking conditions to minimize background while maintaining specific signal, testing different blockers (BSA, casein, commercial blocking buffers) at various concentrations. Develop a standard curve using purified recombinant DHRS13 covering the physiological concentration range in your samples, ensuring parallelism between standard curves and sample dilution curves. Evaluate assay performance metrics including lower limit of detection (LLOD), lower limit of quantification (LLOQ), dynamic range, precision (%CV <20% for intra-assay, <25% for inter-assay), accuracy (80-120% recovery), and dilutional linearity. Test for potential matrix effects by spiking known DHRS13 concentrations into sample matrix and measuring recovery. For clinical or biomarker applications, validate the assay across different sample types (serum, plasma with different anticoagulants, tissue lysates) and assess sample stability under various storage conditions.

How can immunoprecipitation protocols be optimized for studying DHRS13 protein-protein interactions?

Optimizing immunoprecipitation (IP) for DHRS13 interaction studies requires careful consideration of multiple parameters. Select antibodies that recognize native DHRS13 conformation rather than denatured epitopes, as determined by preliminary non-denaturing IP tests. Consider using multiple antibodies targeting different DHRS13 epitopes to avoid missing interactions masked by antibody binding. Optimize lysis conditions using buffers of varying stringency (RIPA, NP-40, digitonin-based) to preserve physiologically relevant interactions while reducing non-specific binding. Include appropriate phosphatase inhibitors when studying DNA damage-induced phosphorylation events . For transient or weak interactions, implement crosslinking strategies (formaldehyde, DSP, or photo-activatable crosslinkers) prior to cell lysis. Consider proximity-dependent biotinylation approaches (BioID, APEX) as complementary methods for capturing the DHRS13 interactome. Control experiments should include isotype-matched control antibodies, DHRS13-depleted cells, and where possible, competitive blocking with immunizing peptides. Validate interactions through reciprocal IP, where the putative interaction partner is immunoprecipitated and DHRS13 is detected by Western blot. For detecting interactions that depend on specific cellular conditions, such as DNA damage, compare IP results from treated versus untreated samples. Analyze immunoprecipitates using mass spectrometry-based proteomics to identify novel interaction partners, followed by validation through orthogonal methods like co-localization studies or functional assays.