DOF1.7 Antibody

What is DOF1.7 and what is its functional significance in plants?

DOF1.7 is a plant-specific transcription factor belonging to the DNA-binding One Zinc Finger (DOF) family. It functions as a transcriptional activator involved in nitrogen deficiency responses in plants, particularly in Arabidopsis thaliana. Recent research has identified DOF1.7 as a direct target of NITRATE-INDUCIBLE GARP-TYPE TRANSCRIPTIONAL REPRESSOR1 (NIGT1) repressors . DOF1.7 plays a critical role in regulating nitrogen deficiency-inducible expression of high-affinity nitrate transporter genes, specifically NRT2.1, NRT2.4, and NRT2.5, which are responsible for most of the soil nitrate uptake activity under nitrogen-deficient conditions .

Unlike NIGT1 repressors which directly suppress multiple nitrate transporter genes under nitrogen-sufficient conditions, DOF1.7 exhibits a more specialized activation pattern - directly activating only NRT2.5 while indirectly and moderately activating NRT2.1 and NRT2.4 under nitrogen-deficient conditions . This targeted regulation contributes to the plant's adaptive response to nitrogen limitation.

What experimental applications utilize DOF1.7 antibodies?

DOF1.7 antibodies serve several critical functions in plant molecular biology research:

• Protein detection and quantification: Western blot analysis to validate DOF1.7 expression levels in transgenic plants, often using epitope tags such as HA for detection .

• Chromatin immunoprecipitation (ChIP) assays: To identify DNA binding sites and target genes of DOF1.7, particularly in the context of nitrogen metabolism regulation.

• Immunolocalization studies: To determine the subcellular localization and tissue-specific expression patterns of DOF1.7.

• Protein-protein interaction studies: To investigate interactions between DOF1.7 and other transcription factors or regulatory proteins in nitrogen signaling pathways.

These applications help researchers elucidate the molecular mechanisms underlying DOF1.7's role in nitrogen metabolism and plant growth regulation.

What are the storage and handling recommendations for DOF1.7 antibodies?

Proper storage and handling of DOF1.7 antibodies are essential for maintaining their functionality and specificity:

• Storage temperature: Store lyophilized antibodies at the recommended temperature (typically -20°C or -80°C for long-term storage) .

• Reconstitution protocol: When reconstituting lyophilized antibodies, use appropriate buffers as recommended by the manufacturer.

• Freeze-thaw cycles: Avoid repeated freeze-thaw cycles as they can degrade antibody quality. Use a manual defrost freezer for storage .

• Shipping conditions: DOF1.7 antibodies are typically shipped at 4°C, but should be stored immediately at the recommended temperature upon receipt .

• Working dilutions: Prepare working dilutions on the day of the experiment to ensure optimal antibody performance.

Following these guidelines helps maintain antibody integrity and ensures reliable experimental results when working with DOF1.7 antibodies.

How does DOF1.7 differentially regulate nitrate transporter genes compared to NIGT1 transcription factors?

DOF1.7 and NIGT1 transcription factors employ distinct regulatory mechanisms in controlling nitrate transporter expression, creating a sophisticated multilayered transcriptional network:

• Differential gene targeting: While NIGT1 repressors directly suppress all three high-affinity nitrate transporter genes (NRT2.1, NRT2.4, and NRT2.5) under nitrogen-sufficient conditions, DOF1.7 exhibits specificity by directly activating only NRT2.5 .

• Regulatory mechanism: DOF1.7 indirectly activates NRT2.1 and NRT2.4, likely by suppressing NIGT1 expression, which releases these genes from NIGT1-mediated repression .

• Conversion of activation types: DOF1.7 converts passive transcriptional activation (relief from NIGT1 repression) into active and potent transcriptional activation, which differentially enhances NRT2 gene expression patterns .

• Temporal dynamics: The interplay between DOF1.7 and NIGT1 creates time-dependent multilayered transcriptional regulation, generating complex expression patterns of nitrogen deficiency-inducible genes .

This differential regulation explains why NRT2 family genes show distinct expression patterns during nitrogen deficiency stress, despite being functionally related. The DOF1.7-NIGT1 regulatory circuit represents a sophisticated adaptation mechanism that allows plants to fine-tune their nitrogen acquisition strategy under varying nitrogen conditions.

What methodological approaches can validate DOF1.7 binding to promoter regions of target genes?

Several complementary approaches can be employed to validate DOF1.7 binding to target gene promoters:

• Chromatin Immunoprecipitation (ChIP):

  • Use DOF1.7-specific antibodies or epitope-tagged versions (e.g., HA-tagged DOF1.7) to immunoprecipitate DOF1.7-bound chromatin.

  • Follow with qPCR targeting specific promoter regions containing putative DOF1.7 binding sites.

  • Analyze enrichment compared to input and negative control regions.

• Electrophoretic Mobility Shift Assay (EMSA):

  • Use purified recombinant DOF1.7 protein and labeled DNA probes from target promoters.

  • Analyze binding by gel shift, with competition assays using unlabeled probes to confirm specificity.

  • Include supershift assays with DOF1.7 antibodies to verify protein identity.

• DNA Affinity Precipitation (DAP):

  • Utilize biotinylated DNA fragments from putative target promoters.

  • Capture with streptavidin beads after incubation with nuclear extracts.

  • Detect DOF1.7 binding by Western blot with specific antibodies.

• Reporter Gene Assays:

  • Create reporter constructs with wild-type and mutated DOF1.7 binding sites.

  • Co-express with DOF1.7 in protoplasts or in planta.

  • Measure reporter activity to assess functional significance of binding.

Research has shown that DOF1.7 binding sites are present in the promoter regions of several key metabolic genes. For example, potential DOF1.7 binding sites have been identified in the promoter regions of PEPC and PK genes in Arabidopsis , confirming its role in coordinating carbon and nitrogen metabolism.

How can researchers differentiate between direct and indirect transcriptional regulation by DOF1.7?

Distinguishing between direct and indirect transcriptional regulation by DOF1.7 requires a multi-faceted experimental approach:

• Time-course expression analysis:

  • Monitor target gene expression at short intervals after DOF1.7 induction.

  • Direct targets typically show rapid expression changes (within hours).

  • Indirect targets show delayed responses.

• Transcription inhibition experiments:

  • Combine DOF1.7 induction with cycloheximide treatment to block new protein synthesis.

  • Direct targets will still respond to DOF1.7 despite translation inhibition.

  • Indirect targets requiring intermediate regulators will not respond.

• Chromatin occupancy studies:

  • Perform ChIP-seq to map genome-wide DOF1.7 binding sites.

  • Correlate binding patterns with transcriptome changes.

  • Direct targets should show both DOF1.7 binding and expression changes.

• Motif analysis:

  • Examine promoters of regulated genes for DOF1.7 binding motifs.

  • Direct targets typically contain consensus binding sites.

  • Perform site-directed mutagenesis to validate functional importance.

Research has demonstrated that DOF1.7 directly activates NRT2.5 but indirectly activates NRT2.1 and NRT2.4 under nitrogen-deficient conditions . This differential regulatory pattern contributes to the complex expression profiles of nitrogen-responsive genes and represents an important adaptive mechanism in plant nitrogen metabolism.

What are the best practices for using DOF1.7 antibodies in Western blot analysis?

Optimizing Western blot protocols for DOF1.7 detection requires careful consideration of several parameters:

• Sample preparation:

  • Isolate nuclei from plant tissues as DOF1.7 is a nuclear-localized transcription factor .

  • Use appropriate extraction buffers with protease inhibitors to prevent degradation.

  • For Arabidopsis, extract nuclear proteins from aerial parts of plants .

• Protein loading and separation:

  • Load 20-30 μg of nuclear protein per lane.

  • Use 10-12% SDS-PAGE gels for optimal separation.

  • Include histone H1 as a nuclear loading control .

• Transfer and blocking conditions:

  • Use PVDF membranes for better protein retention.

  • Block with 5% non-fat dry milk in TBST for 1 hour at room temperature.

  • For phosphorylation studies, use BSA instead of milk.

• Antibody incubation:

  • Primary antibody dilution: Use anti-DOF1.7 at 1:1000 to 1:2000 dilution.

  • If using epitope-tagged DOF1.7 (e.g., HA-tagged), anti-HA antibodies can be used at 1:1000 dilution .

  • Incubate overnight at 4°C for optimal binding.

  • Secondary antibody: Use HRP-conjugated antibodies at 1:5000 to 1:10000 dilution.

• Detection and analysis:

  • Visualize with chemiluminescent substrates for high sensitivity .

  • Include appropriate positive and negative controls.

  • Quantify band intensity using image analysis software normalized to loading controls.

When studying DOF1.7 in transgenic plants, RT-PCR can first confirm transgene expression, followed by Western blotting to verify protein production, as demonstrated in previous studies with HA-tagged DOF1 proteins .

How can researchers design experiments to study DOF1.7's role in nitrogen deficiency responses?

Designing robust experiments to investigate DOF1.7's function in nitrogen deficiency responses requires:

• Genetic manipulation approaches:

  • Generate DOF1.7 overexpression lines using strong constitutive promoters (e.g., 35S) .

  • Create DOF1.7 knockout or knockdown lines using T-DNA insertion mutations or RNAi/CRISPR technologies.

  • Develop inducible expression systems to study temporal effects.

  • Consider epitope tagging (e.g., HA tag) to facilitate protein detection .

• Nitrogen treatment conditions:

  • Design hydroponic or agar plate systems with precise control of nitrogen availability.

  • Include multiple nitrogen conditions: sufficient (e.g., 5-10 mM nitrate), limiting (e.g., 0.5-1 mM), and deficient (e.g., <0.1 mM).

  • Implement time-course experiments to capture dynamic responses.

  • Monitor both short-term responses (hours to days) and long-term adaptation (weeks).

• Phenotypic and physiological analyses:

  • Measure growth parameters (biomass, root architecture, shoot development).

  • Analyze nitrogen content using elementary analysis .

  • Quantify free amino acid levels using HPLC or other analytical methods .

  • Assess carbon metabolites (e.g., glucose levels) to evaluate carbon-nitrogen balance.

• Molecular analyses:

  • Perform RNA-seq to identify DOF1.7-regulated genes.

  • Use ChIP-seq to map DOF1.7 binding sites genome-wide.

  • Employ RT-qPCR to validate expression of key target genes like NRT2.1, NRT2.4, NRT2.5 .

  • Analyze expression of carbon metabolism genes (PEPC, PK) to understand carbon-nitrogen coordination .

• Data integration:

  • Correlate transcriptional changes with metabolic profiles.

  • Compare phenotypic data with molecular responses.

  • Develop models explaining DOF1.7's role in the nitrogen deficiency response network.

Previous research has demonstrated that DOF1 transgenic Arabidopsis plants showed upregulation of genes encoding enzymes for carbon skeleton production, increased amino acid contents, and improved growth under low-nitrogen conditions .

What analytical methods are recommended for assessing DOF1.7's impact on plant metabolism?

Comprehensive analysis of DOF1.7's metabolic effects requires multiple analytical approaches:

• Amino acid profiling:

  • High-Performance Liquid Chromatography (HPLC) for quantification of free amino acids.

  • Gas Chromatography-Mass Spectrometry (GC-MS) for more comprehensive coverage.

  • Target specific amino acids shown to be affected by DOF1.7 expression, including Glu, Gln, Asp, Asn, Arg, and Pro .

  Example data from DOF1 transgenic studies show significant increases in amino acid content:

  Amino Acid	Control (μmol/g FW)	DOF1 Transgenic Line 1 (μmol/g FW)	DOF1 Transgenic Line 2 (μmol/g FW)	DOF1 Transgenic Line 3 (μmol/g FW)
  Arg	3.226 ± 1.162	6.874 ± 3.502*	7.548 ± 3.103*	7.997 ± 2.065*
  Pro	0.366 ± 0.208	1.375 ± 0.211*	1.441 ± 1.209	2.331 ± 1.180*
  Total	17.813 ± 2.413	34.798 ± 9.962*	32.360 ± 11.313*	40.017 ± 6.591*

  *Difference significant by t-test (P < 0.05)

• Carbon metabolite analysis:

  • Enzymatic assays for glucose, sucrose, and starch quantification.

  • Liquid Chromatography-Mass Spectrometry (LC-MS) for broader metabolite profiling.

  • Monitor key organic acids (malate, citrate, α-ketoglutarate) involved in carbon-nitrogen integration.

• Enzyme activity measurements:

  • Spectrophotometric assays for key enzymes in carbon and nitrogen metabolism.

  • Focus on enzymes encoded by DOF1.7 target genes, including:

    • Phosphoenolpyruvate carboxylase (PEPC)

    • Pyruvate kinase (PK)

    • Glutamine synthetase (GS)

    • Nitrate reductase (NR)

• Elemental analysis:

  • Determine total nitrogen content using Kjeldahl method or elemental analyzers.

  • Measure carbon content to calculate C:N ratio.

  • Previous research showed DOF1 expression increased nitrogen content by approximately 30% .

• Flux analysis:

  • Use stable isotope labeling (e.g., 15N, 13C) to track metabolic flux.

  • Quantify nitrate uptake rates using depletion methods.

  • Analyze carbon allocation patterns between different metabolic pathways.

• Transcriptome and proteome analysis:

  • RNA-seq to identify global transcriptional changes.

  • Targeted RT-qPCR for key genes (e.g., NRT2.1, NRT2.4, NRT2.5, PEPC, PK) .

  • Proteomics to detect changes in protein abundance and post-translational modifications.

These analytical methods provide complementary data to construct a comprehensive picture of how DOF1.7 modulates carbon and nitrogen metabolism in plants.

How can researchers validate the specificity of DOF1.7 antibodies?

Ensuring antibody specificity is critical for obtaining reliable results in DOF1.7 research:

• Western blot validation:

  • Compare wild-type plants with DOF1.7 knockout mutants or RNAi lines.

  • Include DOF1.7 overexpression lines as positive controls.

  • Test for cross-reactivity with other DOF family proteins.

  • Use epitope-tagged DOF1.7 (e.g., HA-tagged) and corresponding tag-specific antibodies as reference standards .

• Immunoprecipitation controls:

  • Perform IP with pre-immune serum or non-specific IgG as negative controls.

  • Include input samples (pre-IP lysate) to verify target protein presence.

  • Use DOF1.7 knockout tissues for background assessment.

  • Validate with mass spectrometry to confirm immunoprecipitated protein identity.

• Immunofluorescence validation:

  • Compare staining patterns in wild-type versus knockout tissues.

  • Perform peptide competition assays to verify epitope specificity.

  • Use fluorescently tagged DOF1.7 (e.g., GFP fusion) as localization reference.

  • Confirm nuclear localization consistent with transcription factor function.

• Functional validation:

  • Verify that antibody-detected protein correlates with DOF1.7 function.

  • Test antibody detection in tissues/conditions where DOF1.7 is known to be active.

  • Ensure detection aligns with DOF1.7 mRNA expression patterns.

• Cross-species reactivity testing:

  • If using the antibody across different plant species, validate specificity in each species.

  • Compare sequence conservation of epitope regions across species.

When working with commercial antibodies, researchers should request information on validation methods used by the manufacturer and perform additional validations specific to their experimental system.

What are the critical factors to consider when analyzing DOF1.7's interaction with other transcription factors?

Investigating DOF1.7's interactions with other transcription factors requires careful experimental design:

• Co-immunoprecipitation (Co-IP) approaches:

  • Use DOF1.7-specific antibodies or epitope-tagged versions for pulldown.

  • Include appropriate controls: IgG, unrelated transcription factors, tag-only constructs.

  • Verify interactions by reciprocal Co-IP from both interaction partners.

  • Consider native conditions versus overexpression systems.

• Bimolecular Fluorescence Complementation (BiFC):

  • Fuse DOF1.7 and potential partners to complementary fragments of fluorescent proteins.

  • Include negative controls with known non-interacting proteins.

  • Verify proper subcellular localization (nuclear for transcription factors).

  • Quantify fluorescence intensity to assess interaction strength.

• Yeast two-hybrid (Y2H) screening:

  • Use DOF1.7 as bait to screen for interacting transcription factors.

  • Map interaction domains through deletion constructs.

  • Validate positive hits with alternative methods (Co-IP, BiFC).

  • Test for autoactivation and false positives.

• Chromatin co-occupancy:

  • Perform sequential ChIP (re-ChIP) to detect co-binding of DOF1.7 and other factors.

  • Compare binding patterns from individual ChIP experiments.

  • Analyze enrichment of partner binding motifs near DOF1.7 binding sites.

• Functional consequences of interactions:

  • Test effects on target gene expression when both factors are present versus individually.

  • Analyze whether interactions are competitive, cooperative, or hierarchical.

  • Examine how nitrogen status affects interaction dynamics.

Research suggests potential interactions between DOF1.7 and NIGT1 family proteins within the nitrogen response regulatory network, as DOF1.7 appears to modulate NIGT1 expression and function . Understanding these interactions is crucial for deciphering the multilayered transcriptional regulation of nitrogen metabolism.

How can contradictory results in DOF1.7 studies be reconciled and analyzed?

Addressing contradictory findings in DOF1.7 research requires systematic analysis:

• Experimental context differences:

  • Compare growth conditions (light, temperature, growth media composition).

  • Analyze tissue-specific effects (roots vs. shoots, developmental stages).

  • Evaluate nitrogen status (sufficient vs. deficient) as DOF1.7 function is nitrogen-responsive .

  • Consider genetic background differences between studies.

• Methodological variations:

  • Compare detection methods (antibodies, epitope tags, assay sensitivities).

  • Analyze time points of measurements (acute vs. chronic responses).

  • Evaluate transgene expression levels and patterns.

  • Consider post-translational modifications affecting DOF1.7 function.

• Genetic redundancy considerations:

  • Investigate potential compensation by other DOF family members.

  • Compare single mutant versus higher-order mutant phenotypes.

  • Analyze expression changes of related transcription factors.

• Target gene specificity:

  • Compare promoter sequences of analyzed target genes.

  • Evaluate presence and conservation of DOF1.7 binding motifs.

  • Consider chromatin accessibility differences between experimental systems.

• Physiological state integration:

  • Analyze carbon status alongside nitrogen conditions.

  • Consider interactions with other signaling pathways (hormones, stress responses).

  • Evaluate metabolic feedback effects on DOF1.7 function.

• Data integration approaches:

  • Perform meta-analysis across multiple studies.

  • Use systems biology approaches to model complex regulatory networks.

  • Develop testable hypotheses to explain apparent contradictions.

For example, apparent contradictions in how DOF1.7 regulates different NRT2 genes can be reconciled by understanding the multilayered regulatory mechanism - direct activation of some targets (NRT2.5) and indirect activation of others (NRT2.1, NRT2.4) through suppression of NIGT1 repressors .

What emerging technologies could advance DOF1.7 research?

Several cutting-edge technologies hold promise for deepening our understanding of DOF1.7 function:

• Single-cell technologies:

  • Single-cell RNA-seq to map cell-specific DOF1.7 expression and targets.

  • Single-cell proteomics to analyze protein-level variation.

  • Single-cell metabolomics to connect transcriptional changes to metabolic outcomes.

• Advanced imaging approaches:

  • Live-cell imaging of fluorescently tagged DOF1.7 to track dynamic responses.

  • Super-resolution microscopy to visualize nuclear organization of DOF1.7 complexes.

  • FRET-based sensors to monitor DOF1.7 interactions in real-time.

• Chromatin architecture analysis:

  • Hi-C and related techniques to map DOF1.7's impact on 3D genome organization.

  • ATAC-seq to measure chromatin accessibility changes mediated by DOF1.7.

  • CUT&RUN or CUT&Tag for high-resolution mapping of DOF1.7 binding sites.

• Protein structure and dynamics:

  • AlphaFold2 and related AI tools to predict DOF1.7 structure and interaction interfaces.

  • Hydrogen-deuterium exchange mass spectrometry to map protein interaction surfaces.

  • Cryo-EM to resolve DOF1.7-containing transcriptional complexes.

• Genome editing advancements:

  • Prime editing for precise manipulation of DOF1.7 binding sites.

  • Multiplexed CRISPR approaches to simultaneously modify DOF1.7 and interacting factors.

  • Base editing to introduce specific mutations without double-strand breaks.

• Synthetic biology approaches:

  • Engineer synthetic DOF1.7 variants with altered specificity or activity.

  • Create optogenetic or chemically-inducible DOF1.7 systems for temporal control.

  • Design synthetic regulatory circuits incorporating DOF1.7 for improved nitrogen use efficiency.

These technologies could help resolve outstanding questions about DOF1.7's cell-specific functions, temporal dynamics, and integration within broader regulatory networks controlling plant nitrogen metabolism.

How might DOF1.7 research contribute to improving nitrogen use efficiency in crops?

DOF1.7 research has significant potential applications for agricultural improvement:

• Genetic engineering strategies:

  • Develop DOF1.7 overexpression lines in crop species to enhance nitrogen assimilation.

  • Fine-tune DOF1.7 expression using tissue-specific or nitrogen-responsive promoters.

  • Create crop varieties with optimized DOF1.7 regulation for diverse nitrogen environments.

• Phenotypic outcomes and benefits:

  • Improved growth under low-nitrogen conditions, as demonstrated in Arabidopsis .

  • Enhanced nitrogen content in plant tissues (approximately 30% increase observed) .

  • Increased amino acid production and improved protein content .

• Integration with carbon metabolism:

  • Coordinate carbon and nitrogen metabolism through DOF1.7's regulation of carbon skeleton-producing enzymes (PEPC, PK) .

  • Optimize carbon allocation for amino acid biosynthesis.

  • Balance photosynthetic capacity with nitrogen acquisition.

• Breeding applications:

  • Develop molecular markers based on DOF1.7 sequence or expression patterns.

  • Screen germplasm collections for beneficial DOF1.7 alleles.

  • Incorporate DOF1.7 optimization in breeding programs targeting marginal soils.

• Synergistic approaches:

  • Combine DOF1.7 optimization with improvements in other nitrogen metabolism components.

  • Integrate with root architecture modifications for enhanced nutrient capture.

  • Coordinate with beneficial microbial interactions supporting nitrogen acquisition.

• Environmental benefits:

  • Reduce nitrogen fertilizer requirements through improved plant nitrogen use efficiency.

  • Decrease environmental pollution from nitrogen runoff.

  • Support sustainable agriculture in nitrogen-limited environments.

The regulatory role of DOF1.7 in carbon-nitrogen balance makes it particularly valuable as a target for metabolic engineering, as its manipulation affects multiple aspects of plant metabolism simultaneously .