At4g22110 Antibody

What is At4g22110 Antibody and what organism does it target?

At4g22110 Antibody is a research-grade immunological reagent designed to specifically recognize and bind to the At4g22110 protein in Arabidopsis thaliana (Mouse-ear cress), a model organism widely used in plant molecular biology and genetics research. The antibody targets a protein encoded by the At4g22110 gene locus on chromosome 4 of A. thaliana. This antibody is available as a standardized recombinant product with the product code CSB-PA605730XA01DOA and corresponds to the protein with UniProt ID Q0V7W6.

The methodological significance of this antibody lies in its ability to provide specific detection of the target protein in complex biological matrices, enabling researchers to track protein expression, localization, and interaction networks within plant tissues. When designing experiments with this antibody, researchers should consider the specific isoforms or splice variants of At4g22110 that may exist in their experimental system.

What are the standardized specifications of commercially available At4g22110 Antibody?

The commercially available At4g22110 Antibody is provided with the following standardized specifications:

These standardized specifications ensure experimental reproducibility and reliability across different research settings. When designing experiments, researchers should document the lot number and storage conditions of their antibody preparations, as these factors can influence experimental outcomes. For critical experiments, validation using multiple antibody lots may be advisable to ensure consistency of results.

What are the common applications of At4g22110 Antibody in plant research?

At4g22110 Antibody serves multiple research applications in plant molecular biology:

Localization studies: The antibody can be employed to map protein distribution patterns within different plant tissues and cellular compartments using immunofluorescence or immunohistochemistry techniques. This provides spatial information about protein function within the cellular architecture.

Expression profiling: Researchers can quantify At4g22110 protein levels under varying experimental conditions, such as different abiotic stresses (drought, salinity) or during pathogen exposure, to understand its role in stress responses. This approach complements transcriptomic data to reveal post-transcriptional regulation.

Protein-protein interaction assays: The antibody facilitates identification of binding partners through co-immunoprecipitation (Co-IP) or can be used in conjunction with yeast two-hybrid systems to validate interaction networks. These methods help construct functional protein complexes and pathways.

Gene knockout/knockdown validation: The antibody provides crucial verification of protein absence or reduction in mutant plant lines, confirming the efficacy of genetic modifications. This validation step is essential for establishing causality in functional genomics studies.

Subcellular localization: Determining the precise cellular compartment where At4g22110 resides (organelles, membranes, or cytoplasm) helps inform hypotheses about its biological function. This information guides experimental design for functional characterization studies.

How is At4g22110 Antibody typically validated for experimental use?

While specific validation data for At4g22110 antibody may not be publicly disclosed for proprietary reasons, standard quality control procedures for plant antibodies typically include:

Western blotting validation: The antibody should detect a single predominant band at the expected molecular weight (~25–30 kDa, based on UniProt data) in Arabidopsis thaliana protein extracts. Multiple bands may indicate non-specific binding or detection of post-translationally modified forms of the protein.

Pre-adsorption tests: Signal should be substantially reduced or eliminated when the antibody is pre-incubated with excess purified antigen, demonstrating binding specificity. This control helps confirm that the observed signal is indeed due to specific antigen recognition.

Knockout/knockdown controls: Comparing antibody signals between wild-type plants and those with the target gene knocked out provides strong validation of specificity. The absence or significant reduction of signal in knockout lines confirms antibody specificity.

Cross-reactivity assessment: Testing against protein extracts from non-target species helps establish the antibody's specificity across phylogenetic boundaries. Plant-specific epitopes like At4g22110 generally show minimal cross-reactivity with non-plant species, though this should be experimentally verified.

For rigorous experimental design, researchers should conduct their own validation tests appropriate to their specific experimental conditions and sample preparations.

How can At4g22110 Antibody be optimized for immunolocalization studies in Arabidopsis tissues?

Optimizing At4g22110 Antibody for immunolocalization studies requires careful consideration of several methodological factors:

Fixation protocol selection: Different tissues may require alternative fixation protocols to preserve both antigenicity and cellular architecture. For Arabidopsis tissues, paraformaldehyde (4%) is typically effective, but glutaraldehyde combinations may be necessary for certain cellular compartments. The fixation duration should be optimized to prevent overfixation, which can mask epitopes.

Antigen retrieval optimization: If the target epitope becomes masked during fixation, antigen retrieval steps using citrate buffer (pH 6.0) or enzymatic treatment may be necessary. This is particularly important when targeting membrane-associated or organelle-localized proteins.

Antibody dilution series: Establishing an optimal antibody concentration through a systematic dilution series (typically 1:100 to 1:2000) maximizes signal-to-noise ratio. For At4g22110 Antibody, starting with manufacturer recommendations and optimizing based on signal intensity is advisable.

Signal amplification strategies: For low-abundance proteins, signal amplification using tyramide signal amplification (TSA) or biotin-streptavidin systems may enhance detection sensitivity while maintaining specificity.

Multi-label optimization: When co-localizing At4g22110 with other cellular markers, careful selection of secondary antibodies with non-overlapping emission spectra is essential. Controls for bleed-through and cross-reactivity between secondary antibodies should be included.

Technical validation approaches: Parallel immunolocalization in known At4g22110 mutant/knockout lines provides the strongest validation of signal specificity. Additionally, peptide competition controls, where the primary antibody is pre-incubated with excess antigen peptide, should abolish specific staining.

What are the critical controls and troubleshooting strategies for Western blotting with At4g22110 Antibody?

Successful Western blotting with At4g22110 Antibody requires rigorous controls and troubleshooting strategies:

Essential controls:

• Positive control: Confirmed Arabidopsis thaliana extract with known At4g22110 expression

• Negative control: Protein extract from At4g22110 knockout/knockdown plants

• Loading control: Probing for housekeeping proteins (e.g., actin, tubulin) to normalize expression

• Peptide competition: Pre-incubation of antibody with excess antigen to confirm specificity

Optimization parameters:

• Protein extraction: Special consideration for membrane proteins or nuclear-localized factors may require compartment-specific extraction buffers

• Gel percentage: Based on the predicted molecular weight (~25-30 kDa), 12-15% polyacrylamide gels are recommended

• Transfer conditions: Semi-dry transfer for 45-60 minutes or wet transfer for 1 hour at 100V is typically effective for proteins in this size range

• Blocking conditions: 5% non-fat milk or BSA in TBST, optimized to reduce background without compromising specific signal

• Antibody concentration: Titration series (typically 1:500 to 1:5000) to determine optimal signal-to-noise ratio

Troubleshooting strategies:

• No signal: Check protein transfer efficiency with reversible staining; increase antibody concentration; extend incubation time; verify sample integrity

• Multiple bands: Increase stringency with higher salt concentration in wash buffers; verify tissue-specific isoforms; consider proteolytic degradation

• High background: Increase blocking duration; decrease antibody concentration; add 0.05% Tween-20 to wash buffers; pre-adsorb antibody with non-specific proteins

Special considerations for plant samples:

• Phenolic compounds and secondary metabolites in plant tissues can interfere with protein extraction and antibody binding

• Addition of PVPP (polyvinylpolypyrrolidone), β-mercaptoethanol, and protease inhibitors to extraction buffers can improve results

How can At4g22110 Antibody be implemented in protein-protein interaction studies?

At4g22110 Antibody can be strategically employed in multiple complementary approaches to study protein-protein interactions:

Co-immunoprecipitation (Co-IP) protocols:

• Direct approach: Immobilize At4g22110 Antibody on protein A/G beads to capture the target protein and its interacting partners

• Reverse approach: After immunoprecipitating with antibodies against suspected interaction partners, probe Western blots with At4g22110 Antibody

• Cross-linking optimization: Implementing formaldehyde or DSP (dithiobis(succinimidyl propionate)) cross-linking before lysis can capture transient interactions

Proximity ligation assay (PLA) implementation:

• This technique allows visualization of protein interactions in situ with single-molecule sensitivity

• Requires co-incubation of At4g22110 Antibody with antibodies against potential interaction partners

• Signal amplification through rolling circle amplification provides high sensitivity for detecting even weak interactions

Bimolecular fluorescence complementation (BiFC) validation:

• While not directly using the antibody, BiFC results can be validated by Co-IP experiments with At4g22110 Antibody

• The antibody can confirm expression levels of fusion proteins in BiFC experiments

Mass spectrometry integration:

• Immunoprecipitation with At4g22110 Antibody followed by mass spectrometry analysis identifies interaction partners without prior hypotheses

• Quantitative approaches such as SILAC (Stable Isotope Labeling with Amino acids in Cell culture) or TMT (Tandem Mass Tag) labeling can distinguish genuine interactions from background

Validation strategies:

• Reciprocal Co-IPs with antibodies against identified interaction partners

• Competition assays with recombinant proteins or peptides

• Domain mapping through truncated protein variants

• Confirmation in multiple tissue types or developmental stages to establish biological relevance

What methodological approaches optimize At4g22110 Antibody use in stress response studies?

When investigating stress responses in plants using At4g22110 Antibody, several methodological considerations enhance experimental rigor and data interpretation:

Stress application standardization:

• Define precise stress parameters (intensity, duration, developmental stage) for reproducibility

• Implement gradual versus acute stress application to distinguish adaptive from acute responses

• Document environmental conditions (light, temperature, humidity) that may influence stress responses

Temporal resolution approaches:

• Time-course sampling (0h, 1h, 3h, 6h, 12h, 24h, etc.) to capture dynamic protein expression changes

• Correlation with transcriptional changes to identify post-transcriptional regulation mechanisms

• Pulse-chase experiments to determine protein turnover rates under stress conditions

Spatial distribution analysis:

• Tissue-specific protein extraction to determine organ-specific responses

• Cellular fractionation to track protein translocation between compartments during stress

• In situ immunolocalization to visualize potential changes in subcellular localization

Quantification methodologies:

• Quantitative Western blotting with internal standards for accurate protein level measurements

• ELISA-based approaches for high-throughput quantification across multiple samples

• Image analysis of immunofluorescence data for spatial quantification of protein abundance

Integrative experimental designs:

• Parallel analysis of multiple stressors (drought, salt, heat, pathogens) to identify stress-specific versus general responses

• Combination with phospho-specific antibodies to detect post-translational modifications induced by stress

• Integration with metabolomic data to correlate protein function with metabolic adaptations

Confounding factor controls:

• Age-matched plants for developmental normalization

• Time-of-day controls to account for circadian regulation

• Mock treatment controls subjected to all manipulations except the stress factor

How can contradictory results with At4g22110 Antibody be reconciled in experimental data?

Contradictory results when using At4g22110 Antibody can arise from multiple sources and require systematic troubleshooting approaches:

Epitope accessibility variations:

• Different extraction protocols may expose or mask epitopes

• Post-translational modifications might obscure antibody binding sites

• Protein-protein interactions could shield the epitope in certain cellular contexts

Methodological approach: Compare multiple extraction protocols and denaturing conditions to determine if epitope accessibility is the primary factor. Consider using epitope-tagged versions of the protein in parallel experiments.

Clone-specific recognition patterns:

• If the specific clone or lot of At4g22110 Antibody is not disclosed, batch-to-batch variability could occur

• Different antibody preparations might recognize distinct epitopes or isoforms

Methodological approach: Test multiple lots or sources of antibody against the same samples. If possible, obtain information about the immunogen sequence used to generate the antibody.

Context-dependent protein expression:

• Developmental stage differences between experiments

• Environmental conditions affecting protein abundance

• Circadian rhythm effects on expression patterns

Methodological approach: Implement strict standardization of plant growth conditions, developmental staging, and sampling times. Document all environmental parameters and include appropriate controls in each experiment.

Technical artifacts in immunodetection:

• Non-specific binding to similar proteins

• Cross-reactivity with homologous proteins

• Background signal misinterpreted as specific signal

Methodological approach: Implement peptide competition assays and use knockout/knockdown lines as negative controls. Increase washing stringency and optimize blocking conditions to reduce non-specific interactions.

Data interpretation frameworks:

Methodological approach: Adopt standardized quantification methods with appropriate controls and statistical analysis. Report raw data alongside processed results to enable re-analysis using alternative methods.

How can At4g22110 Antibody facilitate functional genomics studies in Arabidopsis?

At4g22110 Antibody can significantly enhance functional genomics approaches through several methodological implementations:

CRISPR-Cas9 mutation validation strategy:

• The antibody provides protein-level confirmation of gene editing efficiency

• Western blot analysis of CRISPR-targeted lines confirms complete protein knockout or expression of truncated variants

• Immunolocalization in edited tissues can reveal mosaic patterns in chimeric plants

RNAi knockdown quantification:

• Quantitative Western blotting with At4g22110 Antibody allows precise measurement of knockdown efficiency

• Correlation between transcript reduction (qRT-PCR) and protein reduction (immunoblotting) reveals post-transcriptional regulation mechanisms

• Tissue-specific analysis identifies differential knockdown efficiency across plant organs

Overexpression phenotype interpretation:

• The antibody can verify protein accumulation levels in transgenic lines

• Comparing protein levels with phenotypic severity establishes dose-response relationships

• Subcellular localization confirms proper trafficking of overexpressed protein

Protein-DNA interaction studies:

• Chromatin immunoprecipitation (ChIP) using At4g22110 Antibody can identify DNA binding sites if the protein has transcription factor activity

• Sequential ChIP (re-ChIP) approaches can identify multi-protein complexes at specific genomic loci

• Correlation with transcriptome data helps establish regulatory networks

Translational regulation analysis:

• Polysome profiling coupled with At4g22110 Antibody detection can reveal translational regulation

• Ribosome footprinting combined with immunoprecipitation identifies actively translated mRNA populations

These applications collectively provide a multi-dimensional view of gene function beyond sequence-level information, integrating protein dynamics into the functional genomics framework.

What approaches can optimize At4g22110 Antibody for developmental biology research?

Developmental biology research with At4g22110 Antibody requires specialized approaches to capture spatial and temporal protein dynamics:

Developmental stage-specific protocols:

• Optimize fixation and permeabilization for different developmental stages (seedling, vegetative, reproductive)

• Adjust extraction buffers for varying tissue compositions throughout development

• Implement whole-mount immunostaining for intact organ visualization

Tissue-clearing techniques:

• ClearSee or other clearing protocols compatible with immunofluorescence allow deep tissue imaging

• 3D reconstruction of protein distribution patterns across developmental gradients

• Multi-channel imaging with developmental markers establishes temporal-spatial relationships

Live-cell imaging complementation:

• While the antibody is used for fixed tissue analysis, validation with fluorescent protein fusions allows dynamic tracking

• Correlation between fixed-tissue antibody staining and live-cell fluorescent protein localization confirms dynamics

• Photoconvertible fusion proteins provide temporal resolution of protein movement

Developmental perturbation analysis:

• Hormone treatments combined with At4g22110 immunodetection reveal regulatory mechanisms

• Temperature shifts, photoperiod changes, or nutrient availability fluctuations can uncover conditional phenotypes

• Mechanical stimulation effects on protein localization or abundance can be tracked

Quantitative developmental mapping:

• Quantitative image analysis of immunolocalization data creates protein expression maps

• Heat-map representation of protein distribution across developmental stages

• Correlation with transcriptional activity domains using dual labeling approaches

These specialized approaches transform static antibody-based detection into dynamic developmental insights, capturing the fluid nature of plant development at the protein level.

What statistical approaches are recommended for analyzing At4g22110 Antibody data from quantitative studies?

Quantitative data generated using At4g22110 Antibody requires appropriate statistical methods for robust interpretation:

Western blot quantification statistics:

• Normalization strategies: Housekeeping proteins (tubulin, actin) or total protein stains (Ponceau S, Stain-free gels)

• Technical replication: Minimum three technical replicates to account for transfer and detection variability

• Biological replication: At least three independent biological samples recommended

• Statistical tests: ANOVA with post-hoc tests for multiple condition comparisons; t-tests for simple comparisons

• Non-parametric alternatives: Mann-Whitney U or Kruskal-Wallis when normality cannot be assumed

Immunofluorescence quantification:

• Sampling strategy: Define consistent regions of interest (ROIs) across samples

• Background correction methods: Adjacent ROI subtraction or unlabeled sample calibration

• Signal normalization: Against nuclei count, cell area, or reference channel intensity

• Colocalization analysis: Pearson's correlation coefficient, Manders' overlap coefficient, or object-based colocalization

• Distribution analysis: Intensity profiles across cellular compartments or tissue regions

Multi-condition experimental designs:

• Factorial ANOVA for experiments with multiple variables (e.g., genotype × treatment × time)

• Repeated measures ANOVA for time series data from the same samples

• Mixed models for hierarchical experimental designs with nested factors

• Power analysis to determine appropriate sample sizes for detecting biologically relevant differences

Reproducibility enhancement:

• Detailed reporting of all analysis parameters in methods sections

• Data availability statements including raw image files when possible

• Validation of findings using alternative detection methods when available

How can contradictory At4g22110 localization data be reconciled across different experimental systems?

Contradictory localization data is a common challenge in plant molecular biology research. When At4g22110 Antibody yields inconsistent localization patterns, several analytical approaches can help reconcile these differences:

Fixation artifact assessment:

• Compare multiple fixation protocols (paraformaldehyde, glutaraldehyde, methanol) on identical samples

• Implement live-cell imaging with fluorescent protein fusions as a fixation-independent reference

• Cryo-fixation methods can minimize extraction artifacts during sample preparation

Expression level considerations:

• Endogenous versus overexpressed protein may show different localization patterns

• Quantify expression levels across experimental systems to determine threshold effects

• Titrate expression in inducible systems to identify concentration-dependent localization shifts

Developmental context analysis:

• Systematic comparison across developmental stages with standardized imaging parameters

• Time-course studies to capture dynamic relocalization events

• Correlation with tissue differentiation markers to establish developmental context

Stress-induced relocalization:

• Controlled application of mild stresses during sample preparation may trigger artifactual relocalization

• Systematic stress application (oxidative, osmotic, temperature) to determine conditional localization patterns

• Real-time imaging during stress application in live systems to capture authentic responses

Multi-scale imaging approach:

• Correlative light and electron microscopy (CLEM) to resolve subcellular localization ambiguities

• Super-resolution techniques (STED, PALM, STORM) to distinguish closely associated structures

• 3D reconstruction from Z-stacks to resolve apparent contradictions from 2D projections

Biochemical fractionation validation:

• Parallel subcellular fractionation with immunoblotting to confirm microscopy observations

• Quantitative distribution analysis across multiple fractions rather than qualitative presence/absence

• Extraction condition variations to account for differential solubilization of compartments

By systematically implementing these analytical approaches, researchers can distinguish genuine biological variations from technical artifacts, resolving apparent contradictions in At4g22110 localization data.

How might emerging antibody technologies enhance At4g22110 research applications?

Emerging technological advances in antibody development and application hold significant potential for enhancing At4g22110 research:

Single-domain antibodies (nanobodies):

• Development of At4g22110-specific nanobodies could provide superior penetration into plant tissues

• Their smaller size (~15 kDa vs ~150 kDa for conventional antibodies) enables access to sterically hindered epitopes

• Live-cell applications become feasible through direct expression of anti-At4g22110 nanobodies fused to fluorescent proteins

Proximity-dependent labeling integration:

• Antibody-directed targeting of enzymes like BioID or APEX2 to At4g22110 vicinity

• Enables mapping of the proximal proteome around At4g22110 in its native cellular context

• Time-resolved proximity studies to capture dynamic interaction networks

Degradation-inducing antibody technologies:

• PROTAC (PROteolysis TArgeting Chimera) approaches using bifunctional antibody derivatives

• Target At4g22110 for selective degradation without genetic modification

• Temporal control of protein depletion for functional studies

Microfluidic antibody applications:

• High-throughput screening of At4g22110 interactions using antibody-based microfluidic platforms

• Single-cell immunodetection to capture cell-to-cell variability in plant tissues

• Automated image analysis pipelines for quantitative screening applications

Machine learning integration:

• Computational prediction of epitope accessibility under different conditions

• Automated image analysis for subtle localization changes across experimental conditions

• Integration of antibody-derived data with predictive models for protein function

Multiplexed detection systems:

• Simultaneous detection of At4g22110 alongside interacting partners using spectral unmixing

• Mass cytometry (CyTOF) adaptation for plants using metal-conjugated antibodies

• Sequential antibody labeling and elution for highly multiplexed imaging (CODEX, 4i)

These emerging technologies promise to transform At4g22110 research from static observations to dynamic, systems-level understanding of protein function in plant biology.