Target: DPEP1 (UniProt ID: P16444)
Reactivity: Human (primary), with cross-reactivity reported in mouse and rat
Immunogen: Recombinant Human DPEP1 protein (amino acids 23–252)
Specificity: No cross-reactivity with DPEP2 or DPEP3 isoforms .
Sensitivity: Detects DPEP1 at concentrations as low as 0.03 µg/mL in inhibition assays .
PHEV Coronavirus: DPEP1 acts as a functional receptor for porcine hemagglutinating encephalomyelitis virus (PHEV). Overexpression in HEK293T cells increases pseudotype infectivity by >10-fold .
Leukotriene D4 → E4 Conversion: DPEP1 hydrolyzes leukotriene D4, modulating inflammatory responses .
Therapeutic Targeting: Biotinylated antibodies enable tracking of DPEP1 in models of endotoxemia-induced kidney inflammation .
| Vendor | Catalog No. | Host | Applications | Price Range |
|---|---|---|---|---|
| Abbexa | ABIN7149970 | Rabbit | WB, ELISA, IF | $200–$400 |
| Cusabio | CSB-PA007123LD01HU | Rabbit | ELISA | $150–$300 |
| MedChemExpress | HY-P81557 | Rabbit | IHC-P | $250–$450 |
Dipeptidase 1 (DPEP1) is a zinc-dependent metalloproteinase that plays multiple crucial roles in cellular physiology. It belongs to the peptidase M19 family and functions in the hydrolysis of various dipeptides, particularly in renal metabolism. DPEP1 is significant because:
It processes various peptides and antibiotics including thienamycin, penem, and carbapenem derivatives
It participates in glutathione and leukotriene metabolism, converting leukotriene D4 to leukotriene E4
It serves as a regulator of inflammatory mediators including those involved in asthma, arthritis, and inflammatory bowel disease
It has been identified as a marker for colorectal cancer progression
Recent research has discovered it functions as a receptor for coronavirus PHEV
The protein has a molecular weight of approximately 46 kDa and is anchored to cell membranes, making it accessible for antibody-based detection methods in various tissues.
The DPEP1 Antibody, Biotin conjugated reagents typically have the following specifications:
| Attribute | Specification |
|---|---|
| Clonality | Polyclonal |
| Host Species | Rabbit |
| Reactivity | Human |
| Tested Applications | ELISA |
| Immunogen | Recombinant Human Dipeptidase 1 protein (23-252 AA) |
| Isotype | IgG |
| Form | Liquid |
| Purity | > 95% |
| Purification Method | Antigen affinity chromatography |
| Buffer | 0.01 M PBS, pH 7.4, 0.03% Proclin-300 and 50% glycerol |
| Storage | -20°C, avoid repeated freeze/thaw cycles |
| Identifier | UniProt Primary AC: P16444 |
These specifications are critical for determining compatibility with your experimental system and achieving reproducible results .
Proper storage and handling of the DPEP1 Antibody, Biotin conjugated is essential for maintaining its binding specificity and signal strength:
Aliquot the antibody into smaller volumes before freezing to avoid repeated freeze/thaw cycles, which can significantly degrade antibody performance
When creating aliquots, use sterile technique and sterile tubes
Before use, allow the antibody to equilibrate to room temperature gradually
Avoid vortexing the antibody as this can cause denaturation; instead, mix by gentle inversion or flicking
The buffer contains 50% glycerol which helps prevent freezing damage, but proper aliquoting is still recommended
Working dilutions should be prepared fresh before each experiment
The antibody maintains stability for approximately one year when stored properly
Methodologically, it's advisable to run controls with each experiment to verify antibody performance, as even properly stored antibodies can lose activity over time.
While DPEP1 Antibody, Biotin conjugated is primarily validated for ELISA applications, researchers should consider the following methodological approaches for various experimental contexts:
For each application, appropriate positive and negative controls should be included. For colorectal cancer studies, HCT-15 cells have been identified as DPEP1-positive, while specific knock-out or knock-down cell lines would serve as ideal negative controls .
Optimizing DPEP1 Antibody, Biotin conjugated for IHC in cancer tissues requires careful consideration of several methodological factors:
Tissue preparation and fixation:
Staining protocol optimization:
Begin with a 1:500 dilution as reported in literature for DPEP1 antibodies
Use a biotin-based detection system (e.g., avidin-biotin-peroxidase complex)
Block endogenous biotin in tissues (particularly important in liver, kidney, and breast samples)
Consider using tyramide signal amplification for enhanced sensitivity
Scoring system development:
Implement a three-tier system (weak, moderate, or strong) for evaluating DPEP1 expression
Count cells as positive when at least 10% show DPEP1 staining
For tissue microarrays, take the modal score when staining differs between cores
When the modal score is not applicable, the highest score should be used
Validation approaches:
Include known positive tissues (colorectal cancer samples) and negative controls
Consider double staining with proliferation markers like Ki67 to correlate DPEP1 expression with cell cycle activity
This methodological approach has allowed researchers to identify DPEP1 as a marker for the transition from low-grade to high-grade intraepithelial neoplasia in colorectal cancer progression .
For optimal performance in ELISA applications, consider the following methodological guidelines:
Direct ELISA Protocol:
Coat microtiter plate wells with sample containing DPEP1 (typically 1-10 μg/ml in carbonate buffer, pH 9.6)
Incubate overnight at 4°C
Block with 1-5% BSA in PBST for 1-2 hours at room temperature
Add biotin-conjugated DPEP1 antibody at empirically determined dilution
Incubate for 1-2 hours at room temperature
Wash 3-5 times with PBST
Add streptavidin-HRP (typically 1:1000-1:5000 dilution)
Incubate for 30-60 minutes at room temperature
Wash 3-5 times with PBST
Add TMB substrate and monitor color development
Stop reaction with 2N H₂SO₄ or 1N HCl
Read absorbance at 450nm
Sandwich ELISA Considerations:
For sandwich ELISA, use a capture antibody against a different epitope of DPEP1
The biotin-conjugated DPEP1 antibody serves as the detection antibody
Detection ranges of 0.156-10 ng/mL have been reported for DPEP1 ELISA systems
Competitive ELISA Application:
Pre-incubate samples with biotin-conjugated DPEP1 antibody
Add this mixture to wells coated with recombinant DPEP1
Higher concentrations of DPEP1 in samples will result in lower signal
Standard curves should be generated using purified recombinant DPEP1 (23-252 AA)
For all ELISA formats, optimization of antibody concentration through titration is essential for maximizing signal-to-noise ratio and ensuring assay sensitivity.
Research has established DPEP1 as a significant biomarker in cancer progression, particularly in colorectal cancer. Methodological approaches for utilizing the biotin-conjugated antibody in this context include:
Prognostic stratification studies:
Implement IHC analysis of tissue microarrays with standardized scoring systems
Correlate DPEP1 expression with histological staging parameters
Construct receiver operating characteristic (ROC) curves to evaluate prognostic value
Research has demonstrated DPEP1 as an independent adverse prognostic factor with ROC-AUC values of 0.9230 in colorectal cancer
Early neoplastic lesion detection:
Focus on the transition from low-grade to high-grade intraepithelial neoplasia (IEN)
Develop graduated scoring systems for detecting subtle changes in DPEP1 expression
Combine with other markers to create biomarker panels with enhanced specificity
Research methodology has confirmed striking upregulation of DPEP1 in high-grade compared to low-grade IEN
Multiplex biomarker systems:
Combine DPEP1 antibody detection with other cancer markers
Implement double immunostaining with proliferation markers (e.g., Ki67)
Use multiplexed immunofluorescence with streptavidin-conjugated fluorophores
Quantify co-localization using digital image analysis platforms
Detection in liquid biopsies:
Develop protocols for DPEP1 detection in blood, serum, or plasma samples
Utilize the biotin-conjugated antibody in ELISA systems optimized for biological fluids
Combine with exosome isolation for enhanced sensitivity
Detection ranges of 0.156-10 ng/mL provide suitable sensitivity for many biological samples
These methodological approaches leverage the high specificity of DPEP1 antibodies to advance cancer biomarker research beyond simple detection to clinically relevant prognostic and diagnostic applications.
Recent groundbreaking research has identified DPEP1 as a functional receptor for porcine hemagglutinating encephalomyelitis virus (PHEV), opening new avenues for coronavirus research. Methodological approaches for utilizing DPEP1 Antibody, Biotin conjugated in this context include:
Viral receptor binding studies:
Use the antibody to block DPEP1-virus interactions
Implement competition assays between soluble DPEP1 and the antibody
Develop flow cytometry protocols to quantify binding of viral particles to cell surface DPEP1
Research has shown that soluble DPEP1 strongly inhibits PHEV pseudotype infection with IC50 values of 0.03-0.04 μg/mL
Receptor expression profiling in susceptible tissues:
Map DPEP1 expression patterns across tissues using the biotin-conjugated antibody
Correlate expression levels with susceptibility to viral infection
Implement double-staining with viral proteins to visualize co-localization
Both human and porcine DPEP1 orthologs allow viral entry, suggesting conservation of this mechanism
Spike protein interaction mechanism studies:
Develop ELISA-based binding assays using the biotin-conjugated antibody
Implement binding inhibition studies to map interaction domains
Analyze whether the antibody interferes with spike-mediated cell-cell fusion
Research has determined that the enzymatic activity of DPEP1 is dispensable for viral entry, suggesting a structural role in receptor function
Antiviral therapeutic development:
This methodological approach represents a cutting-edge application of DPEP1 antibodies in understanding novel virus-host interactions, with potential implications for coronavirus pathogenesis beyond PHEV.
Addressing specificity concerns requires rigorous validation strategies:
Comprehensive validation approach:
Species cross-reactivity considerations:
While primarily validated against human DPEP1, testing in other species requires validation
Sequence homology analysis between human DPEP1 and orthologs should guide experimental design
The porcine ortholog shares functional conservation with human DPEP1 in virus binding studies
Document any differences in signal intensity or localization patterns between species
Isoform-specific detection:
Consider potential reactivity with DPEP1 isoforms or related family members
The immunogen (23-252 AA) should be evaluated for sequence uniqueness
UniProt database lists secondary accession numbers D3DX80 and Q96AK2, which may represent variant forms
Design experiments to differentiate between closely related peptidases
Tissue-specific interference mitigation:
Address potential interference from endogenous biotin in tissues like liver and kidney
Implement blocking steps using streptavidin/avidin before antibody application
Consider alternative detection systems for tissues with high background
Test multiple sample preparation methods to maximize signal-to-noise ratio
Quantitative validation metrics:
Establish signal-to-noise ratios for different applications
Document antibody titration curves to determine optimal concentration
Implement appropriate statistical analyses to distinguish specific from non-specific signals
Consider multiplexed detection to correlate DPEP1 signal with known co-markers
This comprehensive approach ensures that experimental findings attributed to DPEP1 detection are truly specific and not the result of antibody cross-reactivity with related proteins or non-specific binding.
Researchers frequently encounter several methodological challenges when working with DPEP1 Antibody, Biotin conjugated. Here are evidence-based solutions:
Systematic optimization through pilot experiments addressing each variable independently will yield the most reliable protocol for your specific research application.
Optimizing detection of low-abundance DPEP1 requires methodological refinements at multiple experimental stages:
Sample preparation enhancement:
Implement enrichment strategies for membrane proteins
Consider cell surface protein biotinylation followed by streptavidin pull-down
For tissue samples, use laser capture microdissection to isolate DPEP1-expressing cells
Optimize lysis buffers to effectively solubilize GPI-anchored proteins like DPEP1
Signal amplification technologies:
Implement tyramide signal amplification (TSA) systems for immunohistochemistry
Utilize polymeric detection systems instead of traditional ABC methods
For ELISA applications, consider using poly-HRP conjugated streptavidin
Implement bioorthogonal amplification strategies such as rolling circle amplification
Detection system optimization:
Extend primary antibody incubation times (overnight at 4°C)
Utilize high-sensitivity substrate systems (SuperSignal, ECL Prime)
Implement chemiluminescent substrates with extended signal duration
Consider digital image accumulation for weak signals
Instrument sensitivity maximization:
For microplate readers, utilize extended integration times
Implement PMT gain optimization for flow cytometry applications
For microscopy, use high-sensitivity cameras with cooling systems
Consider spectral unmixing to separate signal from autofluorescence
Validated sensitivity benchmarks:
By systematically implementing these methodological refinements, researchers can achieve detection of DPEP1 even in samples with low expression levels, enabling studies in contexts where DPEP1 dysregulation might be subtle but biologically significant.
Investigating DPEP1 protein-protein interactions requires sophisticated methodological approaches that leverage the biotin conjugation of the antibody:
Proximity-based interaction studies:
Implement proximity ligation assays (PLA) to visualize interactions with <40nm resolution
Combine the biotin-conjugated DPEP1 antibody with antibodies against suspected interaction partners
Utilize PLA to investigate DPEP1 interactions with leukotrienes and carbapenem derivatives
Quantify interaction signals using appropriate image analysis software
Co-immunoprecipitation strategies:
Use streptavidin-coated magnetic beads to pull down the biotin-conjugated antibody-DPEP1 complex
Analyze co-precipitated proteins by mass spectrometry
Implement stringent washing conditions to minimize non-specific interactions
Validate findings with reverse co-immunoprecipitation using antibodies against interaction partners
Functional interaction mapping:
Implement competitive binding assays between DPEP1 and viral proteins like coronavirus spike
Develop dose-response curves for inhibition studies using recombinant proteins
Calculate binding parameters such as IC50 values (0.03-0.04 μg/mL reported for PHEV spike)
Use surface plasmon resonance to determine kinetic parameters of interactions
In situ visualization techniques:
Perform dual-labeling immunofluorescence with DPEP1 and interaction partners
Implement FRET-based assays to confirm direct protein-protein interactions
Utilize super-resolution microscopy (STORM, PALM) to visualize nanoscale interaction domains
Quantify co-localization using appropriate statistical methods (Pearson's correlation, Manders' coefficients)
Dynamic interaction studies:
Develop live-cell imaging protocols using the biotin-conjugated antibody and fluorescent streptavidin
Implement FRAP (Fluorescence Recovery After Photobleaching) to assess interaction dynamics
Utilize pulse-chase experiments to track temporal aspects of interactions
Consider microfluidic approaches for real-time monitoring of binding events
These advanced methodological approaches enable researchers to move beyond simple detection of DPEP1 to understanding its functional interactions in complex biological systems, particularly in contexts like viral binding and cancer progression where protein-protein interactions are mechanistically significant.
Recent advancements have positioned DPEP1 as a significant target in inflammation research, with the biotin-conjugated antibody playing crucial methodological roles:
Neutrophil recruitment mechanisms:
DPEP1 has been identified as an adhesion receptor for neutrophil recruitment in lungs and liver
The biotin-conjugated antibody enables precise localization of DPEP1 at inflammatory sites
Flow cytometric protocols using streptavidin-fluorophore detection systems quantify DPEP1 expression on neutrophils
Blocking experiments with the antibody help elucidate the mechanistic role of DPEP1 in neutrophil extravasation
Anti-inflammatory therapeutic development:
Pharmaceutical compositions targeting DPEP1 are being developed to reduce inflammation
The antibody serves as a validation tool for compound screening assays
Competition assays between potential therapeutics and the antibody help identify binding sites
Patent applications describe DPEP1-binding compositions with potential for inflammatory disease treatment
Leukotriene metabolism regulation:
DPEP1 converts leukotriene D4 to leukotriene E4, regulating inflammatory signaling
The biotin-conjugated antibody enables correlation of DPEP1 expression with leukotriene levels
Enzymatic activity assays combined with immunolocalization reveal functional domains
Inhibitor screening assays identify compounds that modulate DPEP1's metabolic functions
Sepsis and acute kidney injury models:
DPEP1-targeting compositions show promise in treating sepsis-related inflammation
The antibody helps track DPEP1 distribution in kidney tissues during acute injury
Quantitative immunoassays monitor DPEP1 levels as biomarkers of renal inflammatory damage
Therapeutic approaches aim to block DPEP1-mediated leukocyte recruitment in acute scenarios
These cutting-edge applications demonstrate the evolving significance of DPEP1 beyond its classical roles in renal metabolism, positioning the biotin-conjugated antibody as an essential tool in inflammation research.
Integration of DPEP1 antibody detection into multi-omics frameworks requires sophisticated methodological considerations:
Proteogenomic integration strategies:
Correlate DPEP1 protein expression (detected via the antibody) with mRNA expression profiles
Implement CITE-seq approaches combining antibody detection with single-cell transcriptomics
Map DPEP1 expression to genomic variants that may affect protein abundance
Research has demonstrated significant correlation between DPEP1 protein expression and mRNA levels in colorectal cancer, with a ROC-AUC of 0.9230
Glycoproteomics applications:
DPEP1 is a GPI-anchored glycoprotein identified in N-glycoproteome studies
The biotin-conjugated antibody can help verify accessibility of glycosylated epitopes
Combine with lectin-based enrichment to study DPEP1 glycoforms
N-glycosylation site identification dictates accessible epitopes for antibody binding
Spatial multi-omics implementation:
Utilize the biotin-conjugated antibody in spatial proteomics platforms
Correlate DPEP1 localization with tissue metabolomics data
Implement digital spatial profiling to quantify DPEP1 in the context of the tissue microenvironment
Integrate with mass spectrometry imaging for comprehensive spatial mapping
Systems biology framework development:
Position DPEP1 within protein interaction networks using antibody-based interaction studies
Correlate DPEP1 expression with metabolic profiles, particularly leukotriene and glutathione pathways
Develop mathematical models incorporating DPEP1 expression data from antibody-based assays
Implement network pharmacology approaches to predict impacts of DPEP1 modulation
This integrated approach elevates DPEP1 research from isolated protein studies to comprehensive biological understanding, positioning the biotin-conjugated antibody as a bridge between proteomics and other omics domains.
The involvement of DPEP1 in fundamental biological processes offers new avenues for developmental and stem cell research applications:
Pluripotent stem cell surface marker studies:
DPEP1 has been identified in cell surface N-glycoproteome studies of human pluripotent stem cells
The biotin-conjugated antibody enables live cell sorting of stem cell populations
Flow cytometric protocols can identify developmental transitions based on DPEP1 expression
Methodologies for both positive and negative selection using DPEP1 as a marker have been validated
Lineage differentiation tracking:
Monitor DPEP1 expression changes during differentiation of stem cells toward specific lineages
Develop quantitative immunofluorescence protocols for developmental time-course studies
Correlate DPEP1 expression with differentiation stage-specific markers
Implement sorting strategies to isolate DPEP1-expressing cells at critical developmental junctures
Organoid development applications:
Apply the antibody in 3D culture systems to track DPEP1 expression in developing organoids
Establish protocols for whole-mount immunostaining of organoids with the biotin-conjugated antibody
Correlate DPEP1 expression patterns with functional maturation of kidney and intestinal organoids
Implement clearing techniques for deep tissue imaging of DPEP1 in complex 3D structures
Reproductive and developmental toxicology:
Utilize DPEP1 detection as a marker for developmental toxicity in kidney and intestinal tissues
Develop high-throughput screening assays based on DPEP1 expression in embryonic tissues
Implement quantitative image analysis workflows for toxicity assessment
Correlate DPEP1 modulation with developmental outcomes in model organisms
These emerging applications highlight the utility of DPEP1 Antibody, Biotin conjugated beyond traditional research contexts, offering new methodological approaches for understanding developmental processes and stem cell biology.
Based on current research trends and emerging findings, several high-potential research directions stand out:
Viral receptor inhibition studies:
The discovery of DPEP1 as a functional receptor for coronavirus PHEV opens unprecedented research avenues
Future applications will likely focus on developing therapeutic approaches using antibodies or small molecules
Comparative studies of DPEP1 binding across coronavirus species may reveal evolutionary adaptations
Methodological approaches combining structural biology with antibody-based functional studies will be crucial
Cancer progression and metastasis mechanisms:
DPEP1's role in colorectal cancer progression suggests applications in other cancer types
The transition from biomarker to therapeutic target represents a significant opportunity
Combined approaches targeting both diagnosis and treatment based on DPEP1 expression
Development of immunotherapeutic approaches leveraging DPEP1 as a target on cancer cells
Inflammatory disease intervention:
DPEP1's role in neutrophil recruitment and leukotriene metabolism positions it as a therapeutic target
Development of more specific inhibitors based on structural understanding of antibody binding sites
Refinement of biomarker applications in inflammatory conditions beyond current applications
Integration of DPEP1-targeting approaches with existing anti-inflammatory strategies
Advanced imaging and detection technologies:
Development of multiplexed detection systems incorporating DPEP1 with other biomarkers
Implementation of emerging super-resolution techniques for nanoscale localization
Integration with mass cytometry for high-dimensional analysis of DPEP1 in complex tissues
Development of in vivo imaging approaches using modified antibody fragments
These diverse research directions highlight the versatility of DPEP1 Antibody, Biotin conjugated as a tool in biomedical research, with applications spanning from basic molecular understanding to clinical translation.
Emerging technologies will transform how researchers utilize DPEP1 antibodies in several methodological dimensions:
Single-cell and spatial biology integration:
Implementation of DPEP1 antibodies in single-cell proteomics platforms
Development of spatial proteomics approaches combining transcriptomics with DPEP1 protein detection
Integration with emerging spatial multi-omics platforms for comprehensive tissue analysis
Application in microfluidic single-cell analysis systems for high-throughput functional studies
Artificial intelligence and computational biology:
Development of AI-assisted image analysis for quantifying DPEP1 expression in complex tissues
Implementation of machine learning algorithms for predicting DPEP1 interactions based on antibody binding data
Integration of structural biology predictions with antibody epitope mapping
Development of systems biology models incorporating DPEP1 functional data
Antibody engineering advancements:
Creation of recombinant antibody formats with enhanced specificity and reduced background
Development of bi-specific antibodies targeting DPEP1 and interaction partners simultaneously
Implementation of antibody fragments for improved tissue penetration
Creation of switchable antibody systems for temporal control of DPEP1 detection
Translational medicine applications:
Development of companion diagnostic applications based on DPEP1 detection
Implementation in liquid biopsy platforms for non-invasive cancer monitoring
Integration with point-of-care testing systems for inflammatory conditions
Development of theranostic approaches combining DPEP1 detection with therapeutic delivery