6*His Monoclonal Antibody

What is a 6×His tag and why is it commonly used in recombinant protein research?

The 6×His tag (also known as hexahistidine tag, hexa-His, or polyhistidine tag) consists of six consecutive histidine residues (HHHHHH) typically attached to the N- or C-terminal ends of recombinant proteins. This tag is widely used in research for several important reasons:

• Protein purification: The histidine residues have high affinity for nickel and cobalt ions, enabling efficient purification using immobilized metal affinity chromatography (IMAC).

• Minimal impact on protein structure: The small size of the tag reduces interference with protein folding and function.

• Versatility: The tag functions effectively in various expression systems including bacterial, yeast, and mammalian cells.

• Detection: Specific antibodies against the His tag allow for easy detection in multiple applications.

Research has shown that the positioning of the His tag (N- or C-terminal) can affect protein folding, stability, and function, necessitating strategic placement based on protein structure and intended applications .

How do monoclonal antibodies against 6×His tag differ from polyclonal antibodies in research applications?

Monoclonal and polyclonal anti-His tag antibodies differ significantly in their characteristics and optimal research applications:

Monoclonal antibodies like clone HIS.H8, GT359, and AD1.1.10 are preferred in quantitative research applications requiring high specificity and reproducibility . For example, THE™ His Tag Antibody (mAb, Mouse) demonstrates consistent lot-to-lot performance in detecting His-tagged fusion proteins, a critical factor in longitudinal research studies .

What are the different variations of His tag epitopes recognized by commercial antibodies?

Commercial anti-His tag antibodies are engineered to recognize different epitope configurations:

The epitope specificity is a critical consideration during experimental design. For instance, if your recombinant protein contains internal histidine-rich regions, selecting an antibody with the appropriate specificity becomes essential to avoid false positive results. Research has demonstrated that Penta·His antibodies often provide optimal balance between specificity and sensitivity for most laboratory applications .

What factors should be considered when selecting an anti-His tag antibody for specific applications?

When selecting an anti-His tag antibody for a specific application, researchers should consider:

1. Application compatibility:

• Western blot analysis requires antibodies validated for denatured proteins

• Immunoprecipitation requires high-affinity antibodies with minimal background binding

• Flow cytometry and immunofluorescence applications need antibodies that recognize native conformations

2. Clone specificity and validation:

• Examine the clone's validation data in your specific application

• Consider evidence from peer-reviewed publications

• Assess the clone's cross-reactivity profile

3. Sensitivity requirements:

• Different clones exhibit varying detection limits (e.g., GenScript A00186 shows superior sensitivity compared to other commercial antibodies in comparative Western blot analysis)

• Applications requiring detection of low-abundance proteins need high-sensitivity antibodies

4. Conjugation needs:

• Consider whether direct-conjugated antibodies (HRP, biotin, fluorophores) might simplify your workflow

• Evaluate whether secondary detection systems might provide signal amplification advantages

5. Host species compatibility:

• Ensure compatibility with your experimental system to avoid cross-reactivity

• Consider the host species when designing multi-antibody staining panels

Different antibody clones may perform optimally in specific applications; for example, HIS.H8 clone is cited in over 350 publications and functions effectively in Western blot, ICC/IF, IP, and ELISA applications, demonstrating its versatility across multiple techniques .

How should researchers optimize Western blot protocols when using anti-His tag antibodies?

Optimizing Western blot protocols with anti-His tag antibodies requires careful consideration of several parameters:

Sample Preparation:

• Include positive control (known His-tagged protein) and negative control (non-tagged protein)

• For bacterial lysates, consider including reducing agents to expose the His tag epitope

• Optimal protein loading typically ranges from 10-30 μg per lane

Primary Antibody Optimization:

• Perform titration experiments to determine optimal antibody concentration (typically 0.5-2.0 μg/ml)

• Extended primary antibody incubation (overnight at 4°C) often improves signal-to-noise ratio

• Consider using blocking buffer containing 5% dried milk powder to reduce background

Wash Protocol Optimization:

• Multiple washing steps (6 × 5 minutes) with PBS + 0.1% Tween 20 significantly reduces background

• Increasing wash buffer volume improves removal of unbound antibodies

Detection System Selection:

• For low-abundance proteins, consider using signal amplification systems

• For quantitative analysis, fluorescent secondary antibodies provide superior linear range

Sensitivity Comparison:
Western blot sensitivity varies significantly between different anti-His antibody clones. Comparative studies show that THE™ His Antibody from GenScript (A00186) demonstrates superior sensitivity at 0.1 μg/ml concentration compared to other commercial antibodies when detecting the same 6×His-tagged fusion proteins .

What strategies can improve detection of low-abundance His-tagged proteins in complex samples?

Detecting low-abundance His-tagged proteins in complex samples remains challenging but can be optimized through several research-validated approaches:

Pre-enrichment Strategies:

• Small-scale IMAC purification prior to analysis

• Immunoprecipitation using anti-His antibodies to concentrate target proteins

• Size-exclusion chromatography to separate complexity

Signal Amplification Methods:

• Employ biotin-conjugated anti-His antibodies with streptavidin-HRP systems

• Consider tyramide signal amplification (TSA) for immunohistochemistry applications

• Use high-sensitivity ECL substrates for chemiluminescent detection

Antibody Selection and Optimization:

• Compare sensitivity of multiple anti-His antibody clones against your specific protein

• Optimize antibody concentration through careful titration experiments

• Consider cocktails of different anti-His epitope antibodies for enhanced detection

Background Reduction Techniques:

• Extended blocking periods (2-4 hours) with specialized blocking reagents

• Addition of 0.1-0.5% non-ionic detergents to reduce non-specific binding

• Multiple, extensive washing steps between detection phases

Detection System Selection:

• For quantitative applications, near-infrared fluorescent detection systems provide superior linearity and sensitivity

• For extremely low abundance proteins, consider enzyme-mediated chemiluminescence with extended exposure times

Research has demonstrated that certain anti-His antibody clones exhibit significantly higher sensitivity. For example, comparative studies between GenScript (A00186) and Qiagen (34698) antibodies at identical concentrations (0.1 μg/ml) revealed substantial differences in detection thresholds, with the former detecting lower protein quantities across multiple His-tagged constructs .

How can anti-His tag antibodies be integrated into developability assessment workflows for therapeutic proteins?

Anti-His tag antibodies play a crucial role in high-throughput developability assessment of therapeutic proteins, particularly monoclonal antibodies. Integration strategies include:

Early-Stage Screening Applications:

• Identification of expression-positive clones through colony blot screening

• Quantitative assessment of expression levels across multiple constructs

• Rapid assessment of proper folding through comparison of reduced/non-reduced Western blots

Protein Engineering Feedback Loop:

• Detection of His-tagged proteins after sequence engineering modifications

• Assessment of expression level changes following mutation of problematic residues

• Comparison of wild-type versus engineered variant stability characteristics

Biophysical Property Correlation:
Jain et al. (2017) demonstrated that therapeutic antibodies with reduced developability flags showed greater clinical success. High-throughput workflows incorporated anti-His antibodies to detect tagged therapeutic candidates while correlating with critical parameters:

These analyses enable rank-ordering of candidates based on developability criteria prior to advancement into manufacturing processes. Implementation in early discovery enables elimination of problematic sequences before significant resources are invested .

What are the considerations when using anti-His tag antibodies for intracellular detection of fusion proteins?

Intracellular detection of His-tagged proteins introduces several unique research challenges:

Fixation and Permeabilization Optimization:
Two primary fixation protocols yield different results for His-tag detection:

• Formaldehyde fixation (recommended for preserving native protein conformation):

  • 3.5% paraformaldehyde (12 minutes, room temperature)

  • 0.5% Triton X-100 permeabilization (5 minutes)

  • Blocking with 1% NCS in PBS

• Methanol/acetone fixation (recommended for exposing masked epitopes):

  • 1:1 cold methanol:acetone (10 minutes on ice)

  • Blocking with 1% NCS in PBS

Epitope Accessibility Challenges:

• His tags can become buried in protein tertiary structure

• Optimal antibody selection depends on tag position and protein folding

• Tag positioning affects detection efficiency (N-terminal tags often more accessible than C-terminal)

Signal-to-Noise Optimization:

• Extended blocking periods (30+ minutes) significantly reduce background

• Multiple PBS washes (5× after each antibody incubation) essential

• Secondary antibody selection affects background (consider cross-adsorbed antibodies)

Validation Approaches:

• Include transfection controls (non-transfected cells versus His-tagged protein-expressing cells)

• Perform z-stack imaging to confirm intracellular versus surface localization

• Consider dual-labeling approaches to confirm subcellular localization

Flow cytometry data demonstrate successful detection of intracellular His-tagged proteins in CHO cells using THE™ His Tag Antibody, with clear separation between transfected and non-transfected populations .

How can researchers effectively use anti-His tag antibodies for studying protein-protein interactions?

Anti-His tag antibodies offer versatile approaches for investigating protein-protein interactions in research settings:

Co-Immunoprecipitation (Co-IP) Applications:

• Use anti-His tag antibodies conjugated to solid supports for capturing His-tagged "bait" proteins

• Identify novel interaction partners through mass spectrometry analysis of co-precipitated proteins

• Verify specific interactions through reciprocal Co-IP experiments

Pull-down Assay Optimization:

• Immobilize anti-His antibodies on protein A/G beads or directly on activated supports

• Pre-clear lysates to reduce non-specific binding

• Include stringent washing steps to remove weakly-associated proteins

• Consider native elution using His-tag competition versus denaturing elution

Proximity Ligation Assays (PLA):

• Combine anti-His antibodies with antibodies against potential interaction partners

• Detection of protein-protein interactions with subcellular resolution

• Quantification of interaction frequency in different cellular compartments

FRET/BRET Applications:

• Detect His-tagged proteins using fluorophore-conjugated anti-His antibodies

• Measure energy transfer to fluorescently-labeled interaction partners

• Determine interaction kinetics in real-time experiments

Experimental validation of interactions requires careful controls:

• Input control (10% of starting material)

• Negative control (non-His-tagged protein)

• Isotype control (irrelevant antibody of same isotype)

• Competitive inhibition control (excess soluble His peptide)

Research shows anti-His antibodies like AD1.1.10 are highly suitable for immunoprecipitation applications, whereas other clones may demonstrate superior performance in ELISA-based interaction studies .

What are common problems encountered with anti-His tag antibodies and their solutions?

Researchers frequently encounter several challenges when working with anti-His tag antibodies:

High Background Signal:

• Cause: Insufficient blocking, non-specific antibody binding, or endogenous histidine-rich proteins

• Solution: Extend blocking time (1-2 hours), use alternative blocking reagents (BSA vs. milk), increase wash steps, and optimize antibody dilution (typically 0.5-2.0 μg/ml)

Weak or No Signal Detection:

• Cause: Inaccessible His tag, protein degradation, inefficient transfer, or low expression

• Solution: Ensure tag accessibility (try both N and C-terminal detection), add protease inhibitors, optimize transfer conditions, and verify expression with alternative methods

Non-specific Bands in Western Blot:

• Cause: Cross-reactivity with endogenous histidine-rich proteins or antibody degradation

• Solution: Use freshly prepared samples, include reducing agents, run appropriate controls, and compare multiple anti-His antibody clones

Inconsistent Flow Cytometry Results:

• Cause: Inadequate fixation/permeabilization or tag inaccessibility

• Solution: Optimize fixation protocols (formaldehyde vs. methanol/acetone), adjust permeabilization conditions, and consider tag position effects

Variable Immunoprecipitation Efficiency:

• Cause: Competing metal ions, detergent interference, or suboptimal binding conditions

• Solution: Use EDTA-free buffers, optimize detergent concentration, adjust salt concentration, and extend binding incubation time

Research conducted by GenScript demonstrates that lot-to-lot consistency is critical for reproducible results. Figure 4 in their analysis shows consistent anti-His antibody performance across four independent batches when tested against the same His-tagged fusion protein samples, emphasizing the importance of antibody quality in overcoming detection challenges .

How can researchers validate the specificity of anti-His tag antibody detection in their experimental system?

Validation of anti-His tag antibody specificity requires systematic controls and analytical approaches:

Essential Control Experiments:

• Positive and Negative Expression Controls:

  • Positive: Known His-tagged protein with confirmed expression

  • Negative: Non-tagged version of the same protein

  • Negative: Empty vector transfection/transformation

• Tag Position Controls:

  • Test detection with tags in different positions (N-terminal, C-terminal, internal)

  • Compare multiple His-tagged constructs with varying protein contexts

• Antibody Specificity Controls:

  • Competitive inhibition with excess His-peptide (should abolish specific signal)

  • Secondary-only control (no primary antibody)

  • Isotype control (irrelevant antibody of same isotype/species)

Analytical Validation Approaches:

• Multiple Detection Methods:

  • Confirm results using orthogonal detection techniques

  • Compare Western blot, ELISA, and immunofluorescence results

• Mass Spectrometry Verification:

  • Confirm antibody-precipitated proteins contain His-tag sequence

  • Identify potential cross-reacting proteins in your experimental system

• Knockout/Knockdown Validation:

  • Signal should disappear in cells not expressing the His-tagged protein

  • Use inducible expression systems to create controlled expression conditions

Research indicates antibody clone specificity varies; for instance, Western blot analysis comparing N-terminal and C-terminal 6×His-tag fusion proteins revealed that THE™ His Antibody (A00186) effectively recognizes both positions with equivalent sensitivity (1 μg/ml), while other antibodies show positional bias .

What approaches can resolve contradictory results between different anti-His tag antibody clones?

When different anti-His tag antibody clones yield contradictory results, systematic investigation is required:

Analytical Comparison Strategy:

• Side-by-side Clone Comparison:

  • Test multiple antibody clones simultaneously on identical samples

  • Document differences in signal intensity, background, and detection threshold

  • Establish titration curves for each antibody to determine optimal working concentration

• Epitope Accessibility Assessment:

  • Different clones recognize distinct epitopes that may be differentially accessible

  • Compare native versus denatured detection conditions

  • Test antibodies recognizing different His-tag lengths (4×His, 5×His, 6×His)

• Application-specific Performance Evaluation:

  • Some clones perform optimally in specific applications (WB vs. IP vs. IF)

  • Validate each clone in your specific application

  • Consider format-specific optimization (e.g., solution-phase versus solid-phase detection)

Resolution Framework for Contradictory Results:

Comparative analysis of antibody performance reveals significant variation; for example, Western blot sensitivity comparisons between GenScript and Qiagen antibodies at identical concentrations (0.1 μg/ml) demonstrated measurable differences in detection threshold, highlighting the importance of antibody selection for experimental reproducibility .

How are anti-His tag antibodies being applied in high-throughput protein characterization workflows?

Anti-His tag antibodies have become instrumental in high-throughput protein characterization pipelines, particularly in biopharmaceutical research:

Developability Assessment Platforms:
High-throughput screening workflows leverage anti-His antibodies for rapid characterization of hundreds to thousands of candidate molecules. These workflows evaluate critical parameters including:

These assessments require minimal sample quantities (≤1 mg) while generating comprehensive developability profiles that guide candidate selection and engineering .

Automated Platform Integration:

• Array-based detection systems for parallel analysis

• Microfluidic systems for rapid sample processing

• Machine learning algorithms correlating biophysical properties with downstream performance

Research by Jain et al. (2017) demonstrated that antibodies with fewer developability "flags" showed greater clinical success, highlighting the importance of these high-throughput characterization approaches in therapeutic candidate selection .

What are the considerations when using anti-His tag antibodies in multi-parameter flow cytometry?

Multi-parameter flow cytometry with anti-His tag antibodies requires careful experimental design:

Panel Design Considerations:

• Fluorophore Selection: Choose fluorophores with minimal spectral overlap

• Antibody Titration: Determine optimal concentration for each fluorophore-conjugated antibody

• Compensation Controls: Include single-stained controls for each fluorophore

• FMO Controls: Fluorescence Minus One controls establish gating boundaries

His-tag Detection Optimization:

• Fixation/Permeabilization: Optimize conditions based on protein localization (surface vs. intracellular)

• Signal Amplification: Consider secondary detection systems for low-abundance proteins

• Accessibility Assessment: Compare N-terminal versus C-terminal tag detection efficiency

Multi-parameter Analysis Strategy:

• Sequential Gating: Establish logical gating hierarchy for complex populations

• Dimension Reduction: Consider tSNE or UMAP for high-dimensional data visualization

• Batch Effect Control: Include standard samples across experimental runs

Flow cytometry data from THE™ His Tag Antibody studies demonstrate successful detection of His-tagged proteins in transfected CHO cells with clear separation between positive and negative populations, confirming the utility of these antibodies in flow cytometric applications .

How might computational approaches improve anti-His tag antibody selection and application?

Computational approaches are revolutionizing antibody selection and application:

In Silico Prediction Tools:

• Epitope Accessibility Prediction: Structural models predict His-tag exposure in fusion proteins

• Cross-Reactivity Assessment: Algorithmic screening for potential off-target binding sites

• Binding Affinity Prediction: Computational models estimate antibody-epitope interaction strength

Database-Driven Selection:

• Performance Metadata Integration: Centralized repositories of antibody performance characteristics

• Application-Specific Recommendations: Data-driven antibody selection based on experimental parameters

• Clone Comparison Tools: Objective comparison of multiple antibody options

Experimental Design Optimization:

• Assay Condition Modeling: Computational prediction of optimal assay conditions

• Protocol Recommendation Systems: Expert systems suggesting protocol modifications

• Sensitivity Threshold Prediction: Algorithms estimating detection limits for specific antibody-protein combinations

Machine Learning Applications:
The integration of machine learning with biophysical property assessment enables prediction of downstream manufacturing behavior. Systems correlate early-stage antibody characterization data (including anti-His antibody detection profiles) with:

• Production yield in expression systems

• Chromatographic purification efficiency

• Stability during viral inactivation processes

• Performance in ultrafiltration/diafiltration

• Long-term storage stability characteristics

These predictive models enable rational antibody selection and application optimization, potentially reducing experimental iterations and accelerating research timelines .