TSR2 Antibody

What is TSR2 and what are its primary cellular functions?

Recent research has expanded our understanding of TSR2's roles beyond ribosome biogenesis. It has been implicated in microvascular endothelial migration, tube formation, and vascular budding, particularly within the aortic arch . Additionally, TSR2 has been identified as a potential biomarker and therapeutic target in hypertension through its interaction with the PPAR signaling pathway . This emerging role suggests TSR2 may have broader implications in cardiovascular pathophysiology than previously recognized.

What types of TSR2 antibodies are available for research, and what are their characteristics?

Several TSR2 antibodies are available for research applications, each with specific characteristics:

The ab155810 antibody has been cited in published research and has been validated for Western blot applications in multiple cell lines including A549, H1299, HCT116, and MCF7 . The 16263-1-AP antibody has been validated in a broader range of human tissues, including liver, epididymis, heart, kidney, lung, placenta, and spleen tissues for immunohistochemistry applications .

When selecting a TSR2 antibody, consider the specific experimental requirements, including target species, application method, and the cellular compartment of interest. Validate antibody performance in your specific experimental system, as results may vary depending on tissue and cell types.

What are the recommended protocols for using TSR2 antibodies in Western blot applications?

When using TSR2 antibodies for Western blot applications, follow these methodological guidelines based on validated protocols:

• Sample preparation: Prepare whole cell lysates from relevant cell lines. The TSR2 antibody ab155810 has been successfully used with A549, H1299, HCT116, and MCF7 whole cell lysates at 30 μg protein loading .

• Electrophoresis conditions: Use 12% SDS-PAGE for optimal separation, as TSR2 has a predicted molecular weight of 21 kDa .

• Antibody dilution: For ab155810, a dilution of 1:2000 has been validated for Western blot applications . For 16263-1-AP, recommended dilutions range from 1:500 to 1:2000 . Optimal dilution should be determined empirically for each experimental system.

• Detection system: Standard chemiluminescence detection systems are appropriate for visualizing TSR2 bands.

• Expected results: Look for a specific band at approximately 21 kDa, which corresponds to the predicted molecular weight of TSR2 .

If you encounter non-specific bands or weak signal, consider optimizing blocking conditions (5% BSA or milk in TBST), increasing antibody incubation time, or adjusting antibody concentration based on your specific samples.

How should TSR2 antibodies be used in immunohistochemistry and immunofluorescence?

For optimal results in immunohistochemistry (IHC) and immunofluorescence (IF) applications with TSR2 antibodies, follow these methodological recommendations:

For Immunohistochemistry:

• Sample preparation: Use paraffin-embedded tissue sections. The ab155810 antibody has been validated using paraffin-embedded Human Cal27 xenograft tissue .

• Antigen retrieval: For the 16263-1-AP antibody, suggested antigen retrieval should be performed with TE buffer pH 9.0, though citrate buffer pH 6.0 may be used as an alternative .

• Antibody dilution: Use ab155810 at a dilution of 1:500 for IHC applications . For 16263-1-AP, recommended dilutions range from 1:20 to 1:200 .

• Positive control tissues: Human liver, epididymis, heart, kidney, lung, placenta, and spleen tissues have shown positive staining with the 16263-1-AP antibody and can serve as positive controls .

For Immunofluorescence:

• Cell preparation: MCF-7 cells have been validated for IF applications with the 16263-1-AP antibody .

• Fixation: Standard 4% paraformaldehyde fixation for 15-20 minutes at room temperature is typically suitable.

• Permeabilization: Use 0.1-0.3% Triton X-100 in PBS for 5-10 minutes for intracellular proteins.

• Antibody dilution: For 16263-1-AP, recommended dilutions range from 1:200 to 1:800 for IF applications .

• Counterstaining: Use DAPI for nuclear visualization to help determine subcellular localization of TSR2.

For both applications, include appropriate negative controls by omitting the primary antibody or using isotype controls to ensure signal specificity.

What controls should be included when validating TSR2 antibody specificity?

Proper validation of TSR2 antibody specificity requires several controls to ensure reliable and reproducible results:

• Positive controls: Use cell lines or tissues known to express TSR2. The following have been validated:

  • Cell lines: A549, H1299, HCT116, MCF7, and HeLa cells

  • Tissues: Human liver, epididymis, heart, kidney, lung, placenta, and spleen tissues

• Negative controls:

  • Omit primary antibody while maintaining all other steps in the protocol

  • Use isotype control antibodies (e.g., rabbit IgG for rabbit polyclonal antibodies)

  • Include tissues or cell lines with minimal TSR2 expression

• Knockdown/overexpression controls: These are gold standard validation approaches:

  • TSR2 knockdown: Use shRNA targeting TSR2, similar to methods described for other genes . Verify reduced signal with the antibody.

  • TSR2 overexpression: Transfect cells with a TSR2 expression vector and confirm increased signal.

• Peptide competition assay: Pre-incubate the antibody with excess immunizing peptide before application to samples. A specific antibody will show reduced or eliminated signal.

• Multiple antibody comparison: Use different antibodies targeting distinct epitopes of TSR2 to confirm consistent localization and expression patterns.

Documentation of these validation steps is crucial for ensuring experimental rigor and reproducibility in TSR2 research applications.

How can TSR2 antibodies be used to investigate the role of TSR2 in hypertension?

Recent research has implicated TSR2 in hypertension through the PPAR signaling pathway, opening new avenues for cardiovascular research using TSR2 antibodies . Here are methodological approaches to investigate this relationship:

• Expression analysis in hypertension models:

  • Compare TSR2 protein levels between hypertensive and normotensive tissue samples using Western blot analysis with validated TSR2 antibodies .

  • Quantify expression differences and correlate with blood pressure measurements.

  • Perform immunohistochemistry on vascular tissues to analyze localization patterns and expression changes in hypertension.

• Co-immunoprecipitation studies:

  • Use TSR2 antibodies to pull down TSR2 protein complexes from hypertensive vs. normal samples.

  • Analyze interacting partners, particularly components of the PPAR signaling pathway (FABP, PPAR, PLTP, ME1, SCD1, CYP27, etc.) .

  • Validate interactions using reverse co-IP with antibodies against potential binding partners.

• Functional studies in cellular models:

  • Establish hypertension peripheral blood mononuclear cell (PBMC) models as described in the literature .

  • Perform TSR2 knockdown experiments using shRNA approaches and monitor changes in PPAR signaling pathway components using antibodies against key proteins .

  • Similarly, conduct TSR2 overexpression experiments and assess effects on the same pathway components.

• Intracellular signaling analysis:

  • Use phospho-specific antibodies (e.g., for p38, Erk1/2, Akt) in conjunction with TSR2 manipulation to track signaling changes .

  • Apply techniques similar to those used in TLR2 studies, such as EMSA for NF-κB activity assessment and Western blotting for kinase phosphorylation .

For rigorous results, include appropriate controls and consider using multiple techniques to validate findings. The research suggests that TSR2 manipulation significantly influences expression of PPAR pathway proteins, making this a promising area for investigation in hypertension pathophysiology .

What approaches can be used to study the role of TSR2 in ribosome biogenesis?

To investigate TSR2's function in ribosome biogenesis, researchers can utilize the following methodological approaches with TSR2 antibodies:

• Subcellular localization studies:

  • Perform immunofluorescence with TSR2 antibodies alongside markers for nucleolar components.

  • Use subcellular fractionation followed by Western blotting to quantify TSR2 distribution in nuclear, nucleolar, and cytoplasmic fractions.

  • Employ super-resolution microscopy for detailed localization within ribosomal processing compartments.

• Pre-rRNA processing analysis:

  • Perform TSR2 knockdown or overexpression experiments.

  • Use Northern blotting to analyze pre-rRNA processing intermediates.

  • Complement with quantitative PCR to measure levels of specific pre-rRNA species.

  • Correlate changes with TSR2 protein levels determined by Western blotting with TSR2 antibodies.

• Protein-RNA interaction studies:

  • Conduct RNA immunoprecipitation (RIP) using TSR2 antibodies to isolate TSR2-associated RNAs.

  • Analyze bound RNAs by sequencing or RT-PCR to identify specific pre-rRNA regions that interact with TSR2.

  • Cross-validate with in vitro binding assays using recombinant TSR2 protein.

• Protein complex identification:

  • Perform immunoprecipitation with TSR2 antibodies followed by mass spectrometry to identify protein interaction partners in the ribosomal processing machinery.

  • Verify key interactions using reverse co-immunoprecipitation and proximity ligation assays.

  • Map the interaction domains through deletion mutant analysis.

• Functional rescue experiments:

  • Design shRNA-resistant TSR2 expression constructs.

  • Perform knockdown of endogenous TSR2 and express the resistant construct.

  • Assess restoration of normal pre-rRNA processing and ribosome production.

  • Use TSR2 antibodies to confirm knockdown and re-expression efficiency.

How can I troubleshoot non-specific binding or weak signals when using TSR2 antibodies?

When encountering non-specific binding or weak signals with TSR2 antibodies, implement these methodological solutions:

For non-specific binding issues:

• Optimize antibody dilution: Test a range of dilutions to find the optimal concentration. For Western blot, start with the recommended ranges (1:500-1:2000 for 16263-1-AP , 1:2000 for ab155810 ). For IHC, begin with 1:20-1:200 for 16263-1-AP or 1:500 for ab155810 .

• Improve blocking conditions:

  • Extend blocking time to 1-2 hours at room temperature

  • Test different blocking agents (5% BSA, 5% non-fat dry milk, commercial blocking buffers)

  • Add 0.1-0.3% Triton X-100 to reduce hydrophobic interactions

• Increase washing stringency:

  • Use TBST with 0.1-0.3% Tween-20 instead of 0.05%

  • Extend washing times and increase the number of washes

  • Consider adding low concentrations of NaCl (50-150mM) to wash buffers

• Consider cross-reactivity:

  • Pre-adsorb antibody with proteins from the species being tested

  • Use monoclonal antibodies if polyclonal antibodies show high background

For weak signal issues:

• Sample preparation optimization:

  • Ensure proper protein extraction with protease inhibitors

  • For IHC/IF, optimize fixation and antigen retrieval methods (TE buffer pH 9.0 is recommended for 16263-1-AP )

• Increase antibody sensitivity:

  • Use signal amplification systems (HRP polymers, tyramide signal amplification)

  • Extend primary antibody incubation time (overnight at 4°C)

  • Consider more sensitive detection reagents

• Improve target accessibility:

  • For IHC/IF, test alternative antigen retrieval methods

  • For Western blot, ensure complete protein denaturation and optimal transfer conditions

• Verify target expression levels:

  • Confirm TSR2 expression in your samples through RT-PCR

  • Use positive control samples with known TSR2 expression (HeLa, HEK-293, MCF-7 cells )

Keep detailed records of all optimization steps to develop a reproducible protocol for your specific experimental system.

How should I interpret and quantify TSR2 expression data from different experimental approaches?

Proper interpretation and quantification of TSR2 expression data requires methodological rigor and consideration of technique-specific factors:

For Western blot quantification:

• Densitometric analysis:

  • Use software such as ImageJ, Image Lab, or similar to measure band intensities

  • Ensure analysis is performed on non-saturated images

  • Normalize TSR2 signal to appropriate loading controls (β-actin, GAPDH, or tubulin)

• Data presentation:

  • Report relative expression as fold-change compared to control samples

  • Include representative blot images showing both TSR2 and loading control

  • Present quantification as mean ± standard deviation from at least three independent experiments

For immunohistochemistry quantification:

• Scoring methods:

  • Implement H-score system (staining intensity × percentage of positive cells)

  • Use automated image analysis software for unbiased quantification

  • Consider both staining intensity and distribution patterns

  • Employ double-blind scoring by multiple observers

• Comparative analysis:

  • Use consistent scoring criteria across experimental groups

  • Include appropriate positive controls (human liver, kidney, or lung tissue for TSR2 )

  • Report both numeric scores and representative images

For immunofluorescence quantification:

• Image acquisition:

  • Maintain identical exposure settings across all samples

  • Collect z-stack images for accurate intensity measurements

  • Use appropriate filters to minimize autofluorescence

• Signal quantification:

  • Measure mean fluorescence intensity per cell

  • Quantify nuclear vs. cytoplasmic distribution ratios

  • Analyze co-localization with other markers using Pearson's correlation coefficient

For resolving contradictory results:

• Cross-validation approach:

  • Employ multiple detection techniques (WB, IHC, IF, qPCR)

  • Use different antibodies targeting distinct epitopes of TSR2

  • Consider transcript vs. protein level discrepancies that may indicate post-transcriptional regulation

• Biological context considerations:

  • Evaluate results in the context of experimental conditions (stress, disease models)

  • Consider subcellular localization changes that might affect detection

  • Assess potential post-translational modifications that could alter antibody recognition

When publishing, include detailed methodological information including antibody catalog numbers, dilutions, exposure times, and quantification methods to ensure reproducibility .

What statistical approaches are recommended for analyzing TSR2 expression across different experimental conditions?

• Preliminary data assessment:

  • Test for normality using Shapiro-Wilk or Kolmogorov-Smirnov tests

  • Assess homogeneity of variance with Levene's test

  • Identify and appropriately handle outliers (use boxplots or z-scores)

  • Transform data if necessary to meet parametric test assumptions

• For comparing two experimental groups:

  • Use Student's t-test for normally distributed data

  • Apply Mann-Whitney U test for non-parametric data

  • Calculate Cohen's d for effect size estimation

  • Report exact p-values rather than thresholds (e.g., p=0.032 rather than p<0.05)

• For multiple experimental conditions:

  • Apply one-way ANOVA followed by appropriate post-hoc tests (Tukey's HSD for all pairwise comparisons; Dunnett's test when comparing to a control)

  • Use Kruskal-Wallis test with Dunn's post-hoc for non-parametric data

  • Consider ANCOVA when controlling for covariates

  • Report F-statistics, degrees of freedom, and p-values

• For time-course or repeated-measures experiments:

  • Implement repeated-measures ANOVA or mixed-effects models

  • Apply Greenhouse-Geisser correction when sphericity is violated

  • Consider non-linear regression for time-dependent changes

• Correlation and regression analysis:

  • Use Pearson correlation for linear relationships between TSR2 expression and continuous variables (e.g., blood pressure in hypertension studies )

  • Apply Spearman's rank correlation for non-parametric data

  • Consider multiple regression to identify predictors of TSR2 expression

• Advanced statistical approaches:

  • Implement hierarchical clustering for expression pattern analysis

  • Use principal component analysis (PCA) for dimensionality reduction

  • Consider machine learning approaches for complex datasets with multiple variables

• Sample size and power considerations:

  • Conduct a priori power analysis to determine appropriate sample size

  • Report power calculations in methods sections

  • Consider false discovery rate correction for multiple comparisons

When analyzing TSR2 expression in hypertension studies, statistical methods similar to those used in the research by Zang et al. would be appropriate, where they identified differential expression of TSR2 between hypertensive and normotensive samples .

How can computational approaches enhance TSR2 antibody research and application?

Computational tools and approaches can significantly advance TSR2 antibody research, particularly in epitope prediction, antibody engineering, and binding validation:

• Epitope prediction and antibody design:

  • Employ homology modeling to predict the three-dimensional structure of TSR2 protein .

  • Use computational algorithms to identify surface-exposed regions likely to serve as effective epitopes.

  • Apply antibody-specific computational protocols to design high-affinity antibodies against predicted TSR2 epitopes .

  • Implement in silico docking simulations to predict antibody-antigen interactions before laboratory validation .

• Cross-reactivity analysis:

  • Perform sequence alignment across species to identify conserved regions, aiding in predicting cross-reactivity potential.

  • Apply epitope mapping algorithms to assess potential cross-reactivity with similar proteins.

  • Use computational tools to identify potential off-target binding that could lead to non-specific signals.

• Structure-function relationship analysis:

  • Predict binding interface between TSR2 and potential interaction partners.

  • Model the effects of TSR2 mutations on antibody recognition.

  • Simulate post-translational modifications and their impact on epitope accessibility.

• Advanced data analysis:

  • Implement machine learning algorithms for automated image analysis in IHC/IF quantification.

  • Use bioinformatics tools to correlate TSR2 expression with disease states across public databases.

  • Apply network analysis to position TSR2 within relevant signaling pathways (e.g., PPAR pathway in hypertension ).

• Systems biology integration:

  • Integrate TSR2 expression data with transcriptomics, proteomics, and metabolomics datasets.

  • Apply pathway enrichment analysis to contextualize TSR2 function.

  • Model the effects of TSR2 perturbation on cellular systems.

These computational approaches can significantly reduce experimental time and resources by prioritizing the most promising strategies for laboratory validation. The combination of in silico prediction with experimental validation represents a powerful approach for advancing TSR2 antibody research and applications .

What are the potential applications of TSR2 antibodies in clinical and translational research?

TSR2 antibodies hold promising potential for clinical and translational research applications, particularly in the following areas:

• Biomarker development for hypertension:

  • Recent research has identified TSR2 as highly expressed in individuals with hypertension .

  • TSR2 antibodies could be developed for diagnostic immunoassays to assess TSR2 levels in patient samples.

  • Longitudinal studies could evaluate TSR2 as a predictive or prognostic marker for hypertension progression.

  • Correlation studies between TSR2 expression and treatment response could inform personalized medicine approaches.

• Therapeutic target validation:

  • Use TSR2 antibodies to validate the protein's role in disease pathogenesis through immunohistochemical analysis of patient samples.

  • Employ neutralizing antibodies to assess the functional consequences of TSR2 inhibition, similar to approaches used for other targets like TLR2 .

  • Develop antibody-drug conjugates targeting TSR2 if its role in pathology is confirmed.

• Mechanistic studies in disease models:

  • Investigate the relationship between TSR2 and the PPAR signaling pathway in cardiovascular disease models .

  • Assess TSR2 expression in tissue microarrays from various pathological conditions to identify novel disease associations.

  • Study the impact of therapeutic interventions on TSR2 expression and localization.

• Companion diagnostics development:

  • If TSR2-targeted therapies are developed, companion diagnostic assays using TSR2 antibodies could help identify patients most likely to benefit from treatment.

  • Multiplex immunoassays incorporating TSR2 alongside other markers could improve diagnostic accuracy.

• Research tools for ribosome biogenesis disorders:

  • Given TSR2's role in pre-rRNA processing , antibodies could be valuable tools for studying ribosomopathies.

  • Immunohistochemical analysis of patient samples could reveal alterations in TSR2 expression or localization in these disorders.

The potential of TSR2 as a "molecular target for the early diagnosis and precise treatment of hypertension" makes antibodies against this protein particularly valuable tools for translational research . As with any potential biomarker, extensive validation studies would be required before clinical implementation.