C1QTNF9 Antibody, HRP conjugated

What is C1QTNF9 and why is it targeted in research applications?

C1QTNF9 (C1q and Tumor Necrosis Factor Related Protein 9) is a member of the C1q/TNF-related protein family characterized by a distinctive protein structure containing a signal peptide, a collagen-like domain, and a C1q-like globular domain. The protein plays significant roles in metabolic regulation, inflammatory response modulation, and potentially in cardiovascular function. Research interest in C1QTNF9 has grown due to its implications in several physiological and pathological processes.

The protein's full amino acid sequence (333 amino acids in humans) contains multiple domains with distinct functions, making it an important target for research in metabolic and inflammatory disorders . Detection and quantification of C1QTNF9 using specific antibodies enables researchers to investigate its expression patterns, localization, and functional interactions in various experimental contexts.

What are the key applications for HRP-conjugated C1QTNF9 antibodies in experimental workflows?

HRP-conjugated C1QTNF9 antibodies are particularly valuable for multiple detection methodologies that require direct enzymatic signal generation without secondary antibody steps. The primary applications include:

• ELISA (Enzyme-Linked Immunosorbent Assay): The HRP conjugation enables direct detection with chromogenic substrates, making these antibodies ideal for quantitative measurement of C1QTNF9 in serum, plasma, and tissue homogenates with detection limits as low as 0.781 ng/mL .

• Immunohistochemistry (IHC): HRP-conjugated antibodies simplify the detection protocol in tissue sections by eliminating the need for secondary antibodies, providing more consistent staining and reduced background.

• Western Blotting: Direct detection using HRP-conjugated antibodies can improve sensitivity and reduce non-specific binding issues commonly encountered with multi-step detection protocols.

The specific HRP-conjugated C1QTNF9 antibodies targeting amino acids 58-72 have demonstrated particular utility in ELISA applications with human samples, offering a streamlined workflow for protein quantification .

How does epitope selection influence experimental outcomes when using C1QTNF9 antibodies?

Epitope selection (the specific amino acid sequence targeted by the antibody) is a critical determinant of experimental success with C1QTNF9 antibodies. Different functional domains within the protein may be differentially accessible or modified in various experimental contexts:

The epitope choice can significantly impact experimental outcomes because:

• Certain epitopes may be masked by protein folding in native conditions

• Post-translational modifications might alter epitope accessibility

• Protein-protein interactions could obscure specific binding regions

• Processing variants of the protein may lack certain epitopes

Researchers should select antibodies with epitope specificity that aligns with their experimental goals and the likely conformational state of C1QTNF9 in their particular sample types .

What detection range and sensitivity parameters should researchers consider when using HRP-conjugated C1QTNF9 antibodies?

When designing experiments with HRP-conjugated C1QTNF9 antibodies, sensitivity and detection range are critical parameters that determine experimental feasibility and reliability:

• Detection Range: The typical quantitative detection range for C1QTNF9 ELISA assays using HRP-conjugated antibodies is 0.781 ng/mL to 50 ng/mL .

• Minimum Detection Limit (MDL): The threshold sensitivity for C1QTNF9 detection in optimized ELISA systems reaches 0.781 ng/mL, with some advanced systems achieving sensitivity down to 0.469 ng/mL .

• Signal-to-Noise Considerations: Researchers should implement appropriate controls to distinguish specific signal from background, particularly in complex biological matrices where potential cross-reactivity may occur.

When designing experiments, researchers should:

• Perform preliminary dilution series experiments to ensure samples fall within the linear detection range

• Include appropriate standard curves in each experimental run

• Validate detection in their specific sample matrix to account for potential interference effects

These considerations ensure quantitatively reliable results when measuring C1QTNF9 levels in research applications .

How can researchers optimize sample preparation to preserve C1QTNF9 epitope integrity?

Sample preparation significantly impacts the detection efficiency of C1QTNF9 using HRP-conjugated antibodies. Optimization strategies include:

• Protein Extraction Protocols: For tissue homogenates, use buffers containing appropriate protease inhibitors to prevent degradation of C1QTNF9. The collagen-like domain is particularly susceptible to proteolytic cleavage, which can affect antibody recognition, especially for antibodies targeting regions containing amino acids 58-72 .

• Sample Storage Conditions: C1QTNF9 stability is enhanced by storing samples at -80°C and avoiding repeated freeze-thaw cycles. For long-term storage, consider aliquoting samples to minimize degradation.

• Denaturation Considerations: For applications requiring denatured protein (e.g., Western blotting), optimize denaturation conditions carefully. Over-denaturation may destroy conformational epitopes, while insufficient denaturation may leave epitopes inaccessible, particularly affecting antibodies targeting internal regions.

• Fixation Effects in Tissue Samples: For immunohistochemistry applications, fixation methods significantly impact epitope accessibility. Paraformaldehyde fixation may preserve C1QTNF9 structure better than harsher fixatives, particularly when using antibodies targeting amino acids 20-333 .

These optimizations ensure maximal retention of epitope integrity, improving detection sensitivity and specificity across experimental platforms.

What validation strategies confirm specificity of HRP-conjugated C1QTNF9 antibodies?

Rigorous validation is essential before using HRP-conjugated C1QTNF9 antibodies in critical research applications. Recommended validation strategies include:

• Positive and Negative Controls:

  • Positive controls: Use recombinant C1QTNF9 protein or cells/tissues known to express high levels of C1QTNF9

  • Negative controls: Include samples from knockout models or tissues known not to express C1QTNF9

• Competitive Binding Assays: Pre-incubate the antibody with purified recombinant C1QTNF9 before application to samples. Specific binding should be competitively inhibited.

• Multiple Antibody Validation: Compare results using antibodies targeting different epitopes of C1QTNF9 (e.g., AA 1-333 vs. AA 20-333 vs. AA 58-72). Concordant results increase confidence in specificity .

• Cross-Reactivity Assessment: While the antibodies are designed for high specificity, limitations in current technology make comprehensive cross-reactivity testing challenging. Researchers should perform their own validation when working with complex samples that might contain structural analogues of C1QTNF9 .

• Molecular Weight Verification: For Western blotting applications, verification that the detected band matches the expected molecular weight of C1QTNF9 provides additional confirmation of specificity.

These validation approaches collectively build confidence in the specificity of experimental results and help troubleshoot potential issues with non-specific binding.

How do different host species affect C1QTNF9 antibody performance in research applications?

The host species used for antibody generation significantly impacts performance characteristics of anti-C1QTNF9 antibodies:

When selecting C1QTNF9 antibodies, researchers should consider:

• Experimental Sample Origin: Avoid using antibodies from the same species as your experimental samples to prevent endogenous immunoglobulin detection. For mouse samples, rabbit-derived anti-C1QTNF9 antibodies are preferred .

• Multi-labeling Experiments: When performing experiments requiring multiple primary antibodies, selecting antibodies from different host species facilitates discrimination between targets.

• Clonality Considerations: Polyclonal antibodies (available from all three hosts) offer multi-epitope recognition but with potential batch-to-batch variation. The search results indicate that currently available C1QTNF9 antibodies are primarily polyclonal .

• Cross-reactivity Profiles: Based on the search results, rabbit-derived antibodies have demonstrated cross-reactivity with mouse C1QTNF9, which can be advantageous for comparative studies across species .

The host selection should be guided by both the experimental system and the specific application requirements to optimize detection specificity and sensitivity.

What troubleshooting strategies address common challenges with HRP-conjugated C1QTNF9 antibodies?

Researchers frequently encounter technical challenges when working with HRP-conjugated C1QTNF9 antibodies. Evidence-based troubleshooting approaches include:

• High Background Signal:

  • Increase blocking duration and concentration

  • Optimize antibody dilution (typical working dilutions for HRP-conjugated antibodies should be determined empirically)

  • Include additional washing steps with detergent-containing buffer

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

• Weak or No Signal:

  • Verify sample preparation preserves C1QTNF9 integrity

  • Perform antigen retrieval for fixed tissue samples

  • Increase antibody concentration or incubation time

  • Ensure HRP activity is preserved (avoid repeated freeze-thaw cycles)

  • Check substrate freshness and reaction conditions

• Non-specific Binding:

  • Implement more stringent washing procedures

  • Titrate antibody to optimal concentration

  • Use alternative blocking agents (BSA, normal serum, commercial blockers)

  • Filter samples to remove aggregates that may cause non-specific binding

• Inconsistent Results Between Assays:

  • Standardize protein loading and sample preparation

  • Maintain consistent incubation times and temperatures

  • Use internal controls across experiments

  • Prepare larger volumes of working antibody dilutions to use across multiple experiments

These strategies address the most common technical challenges and should be implemented systematically to identify and resolve specific issues in experimental workflows.

How can researchers integrate C1QTNF9 detection in multiplexed immunoassay systems?

Incorporating HRP-conjugated C1QTNF9 antibodies into multiplexed detection systems requires careful consideration of several parameters:

• Enzyme-Substrate Compatibility: When multiplexing, HRP-conjugated C1QTNF9 antibodies require substrates that generate distinguishable signals from other enzymatic reporters. Options include:

  • Chromogenic substrates with distinct absorption spectra

  • Fluorescent substrates with separable emission wavelengths

  • Chemiluminescent substrates with temporal separation

• Cross-Reactivity Mitigation: In multiplexed assays, evaluate potential cross-reactivity between the C1QTNF9 antibody and other target proteins or detection antibodies in the system. Sequential staining protocols may reduce such interactions .

• Signal Optimization: HRP signal amplification strategies such as tyramide signal amplification (TSA) can enhance detection sensitivity when C1QTNF9 is expressed at low levels, but must be carefully controlled to prevent signal bleeding in multiplexed formats.

• Antibody Pairing: When detecting multiple analytes simultaneously, pair the HRP-conjugated C1QTNF9 antibody with additional antibodies raised in different host species to enable discrimination using species-specific secondary reagents .

• Control Systems: Implement appropriate controls to verify that multiplexed detection maintains the sensitivity and specificity demonstrated in single-target detection systems:

  • Single-stain controls to establish baseline signal levels

  • Absorption controls to confirm lack of spectral overlap

  • Epitope competition controls to verify binding specificity

These approaches enable researchers to incorporate C1QTNF9 detection into complex experimental systems that simultaneously measure multiple biomarkers.

What considerations apply when studying post-translational modifications of C1QTNF9?

Post-translational modifications (PTMs) of C1QTNF9 can significantly impact protein function, localization, and detection. When investigating PTMs:

• Epitope Accessibility: Consider how PTMs might mask or expose antibody binding sites. Antibodies targeting amino acids 58-72 or 20-333 may have different sensitivities to PTMs in these regions .

• Modification-Specific Antibodies: Standard C1QTNF9 antibodies detect total protein regardless of modification state. For PTM-specific studies, researchers may need to develop or source antibodies that specifically recognize modified forms of C1QTNF9.

• Sample Preparation Impact: Extraction methods may differentially preserve various PTMs. Phosphorylation is typically well-preserved with phosphatase inhibitors, while glycosylation analysis may require specialized extraction protocols.

• Molecular Weight Shifts: PTMs can alter the apparent molecular weight of C1QTNF9 in gel-based applications. Researchers should consider these potential shifts when interpreting Western blot results:

  • Glycosylation typically increases apparent molecular weight

  • Proteolytic processing decreases apparent molecular weight

  • Phosphorylation may cause subtle shifts detectable on high-resolution gels

• Functional Correlation: When detecting modified C1QTNF9, correlate findings with functional assays to determine the biological significance of the observed modifications.

By carefully addressing these considerations, researchers can generate more comprehensive insights into the biology of C1QTNF9 and its functional regulation through post-translational modifications.

How should researchers design quantitative experiments using HRP-conjugated C1QTNF9 antibodies?

Rigorous experimental design is essential for generating reliable quantitative data with HRP-conjugated C1QTNF9 antibodies:

• Standard Curve Development: For ELISA applications, develop a standard curve using recombinant C1QTNF9 protein covering the full detection range (0.781-50 ng/mL). Use a minimum of 6-8 concentration points with duplicate or triplicate measurements .

• Sample Dilution Strategy: Prepare multiple sample dilutions to ensure readings fall within the linear portion of the standard curve. The recommended dilution series will depend on the expected C1QTNF9 concentration in the specific sample type.

• Controls for Quantitative Analysis:

  • Include positive and negative controls in each experimental run

  • Run internal reference samples across multiple plates/experiments to normalize inter-assay variation

  • Include matrix-matched blank controls to account for background signal

• Data Analysis Approaches:

  • Use appropriate curve-fitting models (4PL or 5PL logistic regression preferred over linear models for ELISA data)

  • Apply statistical tests appropriate for the experimental design

  • Consider the detection limit (0.469-0.781 ng/mL) when interpreting low concentration samples

• Reproducibility Considerations:

  • Technical replicates: Minimum triplicate measurements

  • Biological replicates: Independent samples to account for biological variation

  • Experimental replicates: Repeat key experiments on different days

These rigorous design elements ensure that quantitative measurements of C1QTNF9 using HRP-conjugated antibodies produce reliable and reproducible results suitable for scientific publication.

What are the critical parameters for optimizing immunohistochemistry protocols with C1QTNF9 antibodies?

Successful immunohistochemical detection of C1QTNF9 requires careful optimization of multiple parameters:

• Fixation Method Selection: The choice of fixation significantly impacts epitope preservation and accessibility:

  • Formalin fixation: Requires optimization of antigen retrieval

  • Paraformaldehyde: Often preferable for maintaining protein antigenicity

  • Frozen sections: May preserve native epitopes but with reduced morphology

• Antigen Retrieval Optimization:

  • Heat-induced epitope retrieval (HIER): Test multiple pH conditions (citrate buffer pH 6.0, EDTA buffer pH 9.0)

  • Enzymatic retrieval: May be effective for some C1QTNF9 epitopes in certain tissues

  • Optimize duration and temperature based on tissue type and fixation conditions

• Antibody Selection and Titration:

  • Antibodies targeting amino acids 20-333 or 58-72 have demonstrated utility in IHC applications

  • Perform antibody titration experiments to determine optimal concentration that maximizes specific signal while minimizing background

  • Typical dilution ranges must be determined empirically for each tissue type

• Signal Development Protocol:

  • For HRP-conjugated antibodies, DAB (3,3'-diaminobenzidine) is commonly used

  • Carefully time the development reaction to avoid overdevelopment

  • Consider alternative chromogens for multiplexed detection

• Counterstaining Considerations:

  • Select counterstains that don't obscure C1QTNF9 staining pattern

  • Adjust counterstaining intensity based on C1QTNF9 expression level

These optimization steps ensure reliable visualization of C1QTNF9 distribution in tissue sections while maintaining morphological context.

How can researchers effectively use C1QTNF9 antibodies in comparative studies across species?

C1QTNF9 shows evolutionary conservation across species, creating opportunities for comparative studies. When designing cross-species experiments:

• Sequence Homology Assessment: Before selecting antibodies, analyze sequence homology between target species in the epitope region:

  • The rabbit polyclonal antibody against human C1QTNF9 (AA 20-333) has demonstrated cross-reactivity with mouse samples, indicating conserved epitopes in this region

  • Antibodies targeting the full-length protein (AA 1-333) may offer broader cross-species reactivity

• Validation in Each Species:

  • Cross-reactivity noted in antibody specifications should be experimentally verified

  • Use species-specific positive controls (tissue/cells known to express C1QTNF9)

  • Include appropriate negative controls (preferably knockout or knockdown samples)

• Protocol Adaptation:

  • Optimization may be required for each species (antibody concentration, incubation conditions)

  • Buffer compositions may need adjustment based on tissue composition differences between species

  • Antigen retrieval conditions often require species-specific optimization

• Data Interpretation Considerations:

  • Expression patterns may differ between species due to evolutionary divergence

  • Quantitative comparisons should account for potential differences in antibody affinity across species

  • Functional correlations should consider species-specific roles of C1QTNF9

These approaches enable meaningful cross-species comparisons while minimizing technical artifacts that could confound interpretation of biological differences.

How should researchers interpret apparent discrepancies in C1QTNF9 detection across different methodologies?

Discrepancies in C1QTNF9 detection between different methodological approaches are common and require careful interpretation:

• Epitope Accessibility Variations:

  • Native vs. denatured conditions: Western blotting (denatured) may detect epitopes hidden in ELISA (often native conformation)

  • Different antibodies (AA 1-333 vs. AA 20-333 vs. AA 58-72) may show variable accessibility depending on protein folding and complex formation

• Sensitivity Threshold Differences:

  • ELISA typically offers higher sensitivity (down to 0.469 ng/mL) compared to Western blotting

  • Immunohistochemistry provides spatial information but may have lower sensitivity for low-abundance expression

• Cross-Reactivity Profiles:

  • Different methodologies present distinct opportunities for cross-reactivity

  • Solution-phase assays (ELISA) versus solid-phase detection (WB, IHC) may reveal different cross-reactive species

• PTM Impact on Detection:

  • Tissue-specific or condition-specific post-translational modifications may differentially affect detection by various antibodies

  • Discrepancies between methods may actually reveal biologically relevant protein modifications

• Reconciliation Strategies:

  • Use multiple antibodies targeting different epitopes

  • Implement orthogonal detection methods

  • Correlate findings with functional assays to determine biological relevance

These analytical frameworks help researchers distinguish between technical artifacts and biologically meaningful variations in C1QTNF9 detection across methodological platforms.

What are the best practices for quantifying and statistically analyzing C1QTNF9 expression data?

Robust quantification and statistical analysis of C1QTNF9 expression data requires adherence to best practices:

• Quantification Approaches:

  • For Western blot: Normalize to appropriate loading controls (β-actin, GAPDH) using densitometry

  • For ELISA: Calculate concentrations from standard curves using appropriate regression models (4PL or 5PL)

  • For IHC: Consider both staining intensity and percentage of positive cells (H-score or Allred score)

• Statistical Analysis Selection:

  • For normally distributed data: parametric tests (t-test, ANOVA)

  • For non-normally distributed data: non-parametric alternatives (Mann-Whitney, Kruskal-Wallis)

  • For correlation analysis: Pearson's (linear) or Spearman's (non-linear) correlation coefficients

  • For predictive modeling: regression analysis appropriate to the experimental question

• Sample Size Considerations:

  • Conduct power analysis prior to experimentation to determine appropriate sample size

  • Consider biological variability of C1QTNF9 expression in the tissue/system being studied

  • Ensure sufficient technical replicates (minimum triplicate measurements)

• Reporting Standards:

  • Include measures of central tendency (mean/median) and dispersion (SD/SEM/IQR)

  • Report exact p-values rather than significance thresholds

  • Clarify whether one-tailed or two-tailed tests were employed

  • Include a standardized effect size measurement where appropriate

• Handling Values Near Detection Limits:

  • Develop consistent protocols for handling values near or below the detection limit (0.469-0.781 ng/mL)

  • Consider statistical approaches specifically designed for censored data

How can C1QTNF9 antibodies be employed in studies of protein-protein interactions?

HRP-conjugated C1QTNF9 antibodies can be valuable tools in investigating protein interaction networks:

• Co-Immunoprecipitation Studies:

  • Use unconjugated C1QTNF9 antibodies for pull-down (particularly those validated for IP, like antibodies targeting AA 20-333)

  • Detect interaction partners using standard protein detection methods

  • Verify results with reverse co-IP using antibodies against suspected interaction partners

• Proximity Ligation Assays (PLA):

  • Combine C1QTNF9 antibodies with antibodies against suspected interaction partners

  • PLA generates signal only when proteins are in close proximity (<40nm)

  • Provides spatial information about interaction contexts

• Immunofluorescence Co-localization:

  • Use C1QTNF9 antibodies validated for IF applications (such as those targeting AA 1-333)

  • Combine with antibodies against potential interaction partners

  • Analyze co-localization using appropriate quantitative metrics

• Cross-linking Studies:

  • Chemically cross-link protein complexes in living cells

  • Immunoprecipitate using C1QTNF9 antibodies

  • Identify interaction partners using mass spectrometry

• Functional Validation Approaches:

  • Confirm biological relevance of identified interactions through functional assays

  • Use domain-specific antibodies to map interaction regions

These methodologies can reveal the protein interaction network of C1QTNF9, providing insights into its functional roles in different biological contexts.

What approaches can integrate C1QTNF9 detection with functional assays in translational research?

Integrating C1QTNF9 detection with functional outcomes creates more comprehensive research insights:

• Cell-Based Functional Assays:

  • Correlate C1QTNF9 levels (detected by ELISA or Western blot) with functional readouts:

    • Metabolic parameters (glucose uptake, lipid metabolism)

    • Inflammatory responses (cytokine production, NF-κB activation)

    • Cell signaling pathway activation

• Ex Vivo Tissue Analysis:

  • Combine IHC detection of C1QTNF9 with functional tissue assessments:

    • Tissue metabolic activity (FDG uptake, oxygen consumption)

    • Inflammatory markers in adjacent tissue sections

    • Correlation with clinical parameters in patient samples

• In Vivo Model Systems:

  • Monitor C1QTNF9 levels in circulation (using ELISA with detection range 0.781-50 ng/mL)

  • Correlate with physiological parameters in disease models

  • Use tissue-specific detection to identify sources of circulating C1QTNF9

• Temporal Studies:

  • Track changes in C1QTNF9 expression over time using appropriately validated antibodies

  • Correlate temporal expression patterns with disease progression or response to intervention

  • Use time-course studies to establish causality in observed associations

• Multi-omics Integration:

  • Combine C1QTNF9 protein detection with transcriptomic and proteomic profiling

  • Integrate data using computational approaches to identify regulatory networks

  • Validate key findings using functional assays