UspC plays a crucial role in the cellular response to DNA damage. Specifically, UspC interacts with the Usp domain within the KdpD protein's N-terminal sensing region. This interaction stabilizes the KdpD/KdpE~P/DNA complex, suggesting UspC functions as a scaffolding protein. PMID: 19101563
KEGG: ecj:JW1884
STRING: 316385.ECDH10B_2036
USP antibodies are research tools that detect and study Ubiquitin Specific Proteases, which are deubiquitinating enzymes (DUBs) that remove ubiquitin from target proteins. These enzymes comprise approximately 60% of all DUBs and represent the largest and most varied DUB family . USP antibodies help researchers investigate:
Immune response regulation in tumor microenvironments
Cancer pathways and immunotherapy efficacy
Protein degradation mechanisms
Cell cycle regulation and mitophagy
Endoplasmic reticulum stress responses
Different USP family members (such as USP25, USP30, USP35) have distinct biological functions. For example, USP35 plays roles in "cell cycle regulation, mitophagy or endoplasmic reticulum stress" , while USP25 functions in "inflammation, immune response" and modulates "the Wnt/beta-catenin pathway by deubiquitinating and stabilizing tankyrases" .
The gold standard for USP antibody validation employs an isogenic cell model system:
"The optimal antibody testing methodology involves using an appropriately selected wild type cell and an isogenic CRISPR knockout (KO) version of the same cell as the basis for testing, yielding rigorous and broadly applicable results."
Comprehensive validation includes testing across multiple applications:
Western blot (WB)
Immunoprecipitation (IP)
Immunohistochemistry (IHC)
Immunofluorescence (IF)
A large-scale study assessed 614 commercial antibodies for 65 neuroscience-related proteins using this approach, providing important benchmarks for antibody performance . This standardized characterization process allows side-by-side comparison of antibodies against the same target from multiple vendors.
Based on manufacturer specifications, different USP antibodies have optimized conditions for various applications. For example:
| USP Antibody | Application | Recommended Dilution | Validated Cell Types/Tissues |
|---|---|---|---|
| USP25 (12199-1-AP) | Western Blot | 1:500-1:2000 | BxPC-3 cells, mouse cerebellum tissue, K-562 cells |
| USP25 (12199-1-AP) | Immunoprecipitation | 0.5-4.0 μg for 1.0-3.0 mg protein | RAW 264.7 cells |
| USP25 (12199-1-AP) | Immunohistochemistry | 1:200-1:800 | Human lung cancer tissue |
| USP35 (ab254939) | IHC-P, ICC/IF | Not specified | Human samples |
Importantly, manufacturers emphasize: "It is recommended that this reagent should be titrated in each testing system to obtain optimal results" as performance can be "Sample-dependent" .
Antibody performance often varies dramatically between applications. Research has shown limited correlation between an antibody's performance in different techniques . To address this variability:
Perform application-specific validation: An antibody that works well in Western blot may fail in immunofluorescence.
Test multiple antibodies: When possible, evaluate multiple antibodies against the same target:
"Side-by-side comparisons of all antibodies against each target, obtained from multiple commercial partners" provides the most reliable assessment .
Include proper controls: For each application, include positive controls (cell lines known to express the target) and negative controls (knockout cells or isotype controls).
Standardize protocols: Develop detailed protocols with all critical parameters specified.
Use reference standards: Incorporate USP monoclonal antibody reference standards as controls when possible .
USPs play significant roles in cancer immunotherapy by "regulating immune cell function and immune response in tumor microenvironment (TME)" . When studying USPs in cancer:
Select appropriate model systems:
Choose cell lines based on target expression levels
Consider cancer models relevant to the specific USP being studied
Validate antibody specificity in each model system
Consider combinatorial approaches:
Studies have shown that USP inhibitors combined with other therapies can yield synergistic effects. For example, "When used in combination, an adenovirus-based vaccine and P5091 (USP7 inhibitor) in a mouse CT26 xenograft model displayed better outcomes than either drug used alone" .
Assess relevant functional outcomes:
Cytokine production (e.g., IFN-γ, TNF-α, IL-10)
Immune cell infiltration and activity
Tumor growth parameters
Integrate genomic and proteomic data:
Correlate antibody-based detection with RNA expression data when possible to strengthen findings.
Discriminating between related USP proteins requires careful experimental design:
Epitope selection: Choose antibodies targeting unique regions not conserved across USP family members.
Validation in knockout systems: Use CRISPR-Cas9 generated knockout cells for each specific USP protein.
Expression profiling: Consider tissue-specific expression patterns. For example:
Confirmatory techniques: Employ orthogonal methods like mass spectrometry or RNA analysis to confirm antibody specificity.
Dilution optimization: Test antibody dilution series to maximize specific binding while minimizing cross-reactivity.
USP proteins often have high molecular weights and complex post-translational modifications, requiring specific Western blot optimization:
Sample preparation:
Use appropriate lysis buffers (often containing deubiquitinase inhibitors)
Ensure complete protein denaturation for accurate molecular weight detection
Include protease and phosphatase inhibitors
Gel selection and transfer conditions:
Antibody dilution optimization:
Detection method selection:
Choose detection system based on expected protein abundance
Consider enhanced chemiluminescence for low abundance targets
Controls:
For reliable immunohistochemistry results with USP antibodies:
Optimize antigen retrieval:
Specific conditions are often required; for example, USP25 antibody validation suggests "antigen retrieval with TE buffer pH 9.0" with an alternative option of "citrate buffer pH 6.0" .
Titrate antibody concentration:
Test a dilution series (e.g., 1:200-1:800 for USP25 in IHC ).
Include appropriate controls:
Positive control tissues known to express the target
Negative controls (omitting primary antibody)
Isotype controls to assess non-specific binding
Validate staining pattern:
Compare with expected subcellular localization
Assess specificity using knockout/knockdown tissues when available
Optimize detection system:
Select appropriate secondary antibodies and visualization methods based on target abundance and tissue type.
Maintaining reproducibility requires systematic approaches:
Standardize protocols:
Develop detailed SOPs covering all experimental steps, from sample preparation to data analysis.
Document antibody information:
Record catalog numbers, lot numbers, dilutions, and incubation conditions.
Use reference standards:
"USP monoclonal antibody reference standards...can be used for many purposes including: as an independent control material for method development, training, and method transfer; as an internal assay control" .
Implement quality control measures:
Regularly test antibody performance using control samples.
Cross-validate results:
Use multiple antibodies against the same target when possible.
Compare with orthogonal methods:
Correlate antibody-based results with RNA expression or mass spectrometry data.
Size exclusion chromatography (SEC) is critical for ensuring antibody quality in USP research:
"SEC can be used to measure LMW variants, monomer, and high-molecular weight (HMW) variants in the same analysis yielding a measure of monomeric purity. [It] robustly differentiates between Monomer, HMWS (aggregates) and LMWS (fragments)."
| Analytical Parameter | System Suitability Criteria |
|---|---|
| Chromatographic similarity | Consistent peak profiles |
| Consistency of chromatogram | Stability in bracketing injections |
| % Peak area | Main peak: 99.1%–99.6% |
| HMWS (aggregates) | 0.4% – 0.67% |
| LMWS (fragments) | Not more than 0.2% |
SEC analysis ensures antibody reagent quality, which is essential because "antibody aggregation can lead to immunogenicity" and ">99% purity is crucial" .
The transition from traditional HPLC to UHPLC methods has further improved analysis:
"UHPLC is an advanced separation technique that allows for shorter run times, less amount of sample, better chromatographic separation, and increased throughput as compared to traditional HPLC."
USP has developed four monoclonal antibody Reference Standards:
mAb System Suitability
mAb 001
mAb 002
mAb 003
These standards provide "a range of reference materials with different physico-chemical properties" and are characterized by:
| Characteristic | Description |
|---|---|
| Antibody class | Recombinant humanized IgG1s |
| Expression system | Chinese hamster ovary (CHO) cell culture |
| Manufacturing | Industry standard upstream production and downstream purification |
| Testing | Rigorous collaborative testing using USP General Chapter <129> methods |
| Additional characterization | N-glycans, sialic acid, intact mass, sequence identification by peptide mapping, and post-translational modifications |
These standards serve multiple purposes:
"Independent control material for method development, training, and method transfer"
"Internal assay control"
"Standardization of physico-chemical testing, such as intact mass, charge heterogeneity, size variants, purity, and glycan analyses"
USP monoclonal antibody reference standards undergo comprehensive characterization:
| Analytical Method | Quality Attribute | Results for Reference Standards |
|---|---|---|
| SEC-HPLC | Size variants | mAb 001: HMWS 1.1%, Main Peak 98.9%, LMWS <0.1% mAb 002: HMWS 0.7%, Main Peak 99.2%, LMWS <0.1% mAb 003: HMWS 0.4%, Main Peak 99.5%, LMWS 0.1% |
| SEC-UHPLC | Size variants | mAb 001: HMWS 0.7%, Main Peak 99.3%, LMWS <0.1% mAb 002: HMWS 0.9%, Main Peak 99.1%, LMWS <0.1% mAb 003: HMWS 0.4%, Main Peak 99.6%, LMWS <0.1% |
| N-Glycan Analysis (CE-LIF) | Glycan distribution | mAb 001: G2F 5.04%, G1Fb 9.16%, G1Fa 27.86%, G0F 49.87% mAb 002: G2F 1.78%, G1Fb 5.42%, G1Fa 15.31%, G0F 70.56% mAb 003: G2F 4.24%, G1Fb 7.67%, G1Fa 25.20%, G0F 54.18% |
| PTM Analysis | Post-translational modifications | mAb 001: LC N-term Pyro Glu 95.9%, HC N-term Pyro Glu 98.7% mAb 002: LC N-term Pyro Glu -, HC N-term Pyro Glu 1.1% mAb 003: LC N-term Pyro Glu -, HC N-term Pyro Glu 1.5% |
| Sialic Acid Analysis | Sialylation | mAb 001: Neu5Ac/protein 0.05 nmol/nmol mAb 002: Neu5Ac/protein 0.02 nmol/nmol mAb 003: Neu5Ac/protein 0.03 nmol/nmol |
HMWS = High Molecular Weight Species, LMWS = Low Molecular Weight Species
USP antibodies serve several critical functions in cancer research:
Expression profiling:
Detect and quantify USP expression in tumor versus normal tissues.
Mechanistic studies:
"USPs can regulate the efficacy of immunotherapy through modulating immune cell function and immune response in tumor microenvironment (TME)" . Antibodies help track these mechanisms.
Therapeutic target validation:
For example, "USP7 inhibition was capable of potentiating the efficacy exhibited by the adenovirus-based tumor vaccine and the anti-PD-1 monoclonal antibody therapy in mice with TC1 lung tumor" .
Biomarker development:
Studies like those examining Trop-2 expression in Uterine Serous Papillary Carcinoma used antibody-based methods including "immunohistochemistry (IHC) in a total of 23 USPC" and "flow cytometry and real-time-PCR" .
Therapeutic antibody development:
Research on humanized anti-Trop-2 monoclonal antibody (hRS7) demonstrated "a high level of antibody-dependent cellular cytotoxicity (ADCC)" against cancer cells.
USP proteins have emerged as important factors in neurological disorders:
A major antibody validation study focused on "65 neuroscience-related proteins" including:
"32 Alzheimer's disease (AD)-related proteins"
"22 proteins nominated within the amyotrophic lateral sclerosis (ALS) Reproducible Antibody Platform project"
This focus indicates the importance of USP proteins in:
Neurodegenerative disease mechanisms
Protein quality control in neurons
Neuroinflammatory processes
Researchers use USP antibodies to:
Map expression patterns in neural tissues
Study protein degradation pathways in neurodegeneration
Investigate potential therapeutic targets
Develop biomarkers for neurological disorders
Important regional differences exist in antibody patent protection:
| Aspect | European Approach | US Approach |
|---|---|---|
| Functional claims | "In Europe it is possible to obtain broad functional antibody claims" | "In the US it is becoming increasingly difficult to obtain protection for antibodies on the basis of functional claims" |
| Skilled person standard | Skilled person considered to have "a much higher level of knowledge" | Skilled person considered to have "a relatively low level of knowledge" |
| Disclosure requirements | Lower bar for "sufficiency of disclosure" | "Relatively high level of disclosure" required |
| Inventiveness standard | "More challenging to show that a claimed antibody is inventive" | Relatively easier to establish non-obviousness |
| Functional advantages | "Functional antibody claims may be considered inventive if the function is surprising or advantageous" | Function alone generally insufficient |
These differences impact how researchers should document and publish work on novel antibodies when patent protection is a consideration .
Modern antibody discovery involves sophisticated methodologies:
Target research:
"Extensive basic research to understand the target antigen thoroughly. Researchers study its structure, function, and role in various diseases."
Antibody generation approaches:
Screening technologies:
"High-throughput screening techniques...allow for the rapid assessment of a large number of antibodies in various formats"
Characterization and optimization:
"Rigorous characterization, where binding properties and functional attributes are assessed...determining the epitope specificity and the ability to bind to the antigen with high affinity"
Validation in biological systems:
"Preclinical studies, often involving in vitro and in vivo experiments, assess the antibodies' performance in realistic biological systems"
The newest approach combines traditional antibody generation with genetic engineering:
"USC scientists have discovered a way to turn the body's B cells into tiny surveillance machines and antibody factories that can pump out specially designed antibodies to destroy cancer cells or HIV" .