MID1IP1 Antibody, FITC conjugated

What is MID1IP1 and what are its primary cellular functions?

MID1IP1, also known as Gastrulation-specific G12-like protein, Mid1-interacting G12-like protein, or Spot 14-related protein (S14R), is a 183 amino acid protein belonging to the SPOT14 family . This protein plays several important biological roles:

• Regulation of lipogenesis, particularly in the liver

• Involvement in the biosynthesis of triglycerides with medium-length fatty acid chains

• Modulation of lipogenesis by interacting with acetyl-CoA carboxylase (ACACA)

• May function as a transcriptional coactivator

MID1IP1 has a molecular weight of approximately 20 kDa, though it may be observed at 23 kDa and 46 kDa in some experimental conditions, with the latter potentially representing dimerized forms . The protein can localize to both the nucleus and cytoplasm, and may form homodimers in the absence of THRSP (Thyroid hormone-responsive protein) .

How does FITC conjugation affect antibody functionality and applications?

FITC conjugation involves the chemical attachment of fluorescein isothiocyanate to antibodies, creating a fluorescent-labeled immunoglobulin. This process:

• Enables direct visualization of antibody binding through fluorescence microscopy, flow cytometry, and other fluorescence-based techniques

• Adds a fluorescent tag with excitation/emission spectra of approximately 495 nm/520 nm, producing green fluorescence

• May slightly alter the antibody's binding characteristics compared to unconjugated versions

The conjugation process is highly dependent on reaction conditions, including:

• pH (optimal at approximately 9.5)

• Temperature (room temperature provides efficient labeling)

• Protein concentration (25 mg/ml initial concentration is effective)

• Reaction time (maximal labeling typically occurs within 30-60 minutes)

Over-labeling can potentially affect antibody functionality, which is why optimally labeled antibodies are often separated from under- and over-labeled proteins through techniques like gradient DEAE Sephadex chromatography .

What are the recommended storage conditions for maintaining MID1IP1 Antibody, FITC conjugated activity?

Proper storage is critical for maintaining antibody activity and fluorescence intensity:

• Store at -20°C for long-term preservation

• Some preparations may be refrigerated at 2-8°C for up to 6 months

• Avoid repeated freeze-thaw cycles as they can degrade antibody quality and reduce fluorescence

• Store in appropriate buffer systems, typically containing preservatives like 0.03% Proclin 300 or 0.09% sodium azide

• Some formulations include stabilizers such as 50% glycerol and PBS at pH 7.4

For optimal results, aliquot the antibody upon receipt to minimize freeze-thaw cycles. When handling FITC-conjugated antibodies, protect from light to prevent photobleaching of the fluorophore.

What controls should be included when using MID1IP1 Antibody, FITC conjugated in flow cytometry experiments?

When designing flow cytometry experiments with FITC-conjugated MID1IP1 antibodies, several controls are essential:

• Negative Controls:

  • Isotype control (FITC-conjugated rabbit IgG with no specific target)

  • Unstained cells (to establish autofluorescence baseline)

  • Secondary antibody only (if using an indirect staining method)

• Positive Controls:

  • Cell lines with verified MID1IP1 expression (e.g., HEK-293 cells show positive expression)

  • Transfected cells overexpressing MID1IP1 (as demonstrated in Lane 2 of Western blot validations)

• Gating Controls:

  • Single-color controls for compensation when performing multi-color flow cytometry

  • FMO (Fluorescence Minus One) controls to establish gating boundaries

As shown in flow cytometric analysis of 293 cells using MID1IP1 antibody, there is a clear shift in fluorescence intensity between negative controls (left histogram) and MID1IP1-positive samples (right histogram) . This demonstrates the specificity of the antibody and establishes a reliable gating strategy.

What dilution factors are recommended for different applications of MID1IP1 Antibody, FITC conjugated?

Optimal dilution factors vary by application technique:

These dilutions serve as starting points, and researchers should conduct titration experiments to determine optimal concentrations for their specific experimental conditions. The antibody's performance can vary based on sample type, fixation method, and detection system used .

What sample preparation methods optimize MID1IP1 detection in different tissue types?

Effective sample preparation is crucial for accurate MID1IP1 detection:

For Flow Cytometry:

• Single-cell suspensions should be fixed with 2-4% paraformaldehyde

• Permeabilization may be necessary for intracellular staining

• Cell concentration should be adjusted to 1×10^6 cells/mL for optimal results

For Immunohistochemistry:

• Formalin-fixed, paraffin-embedded tissues require antigen retrieval

• Human stomach tissue shows reliable staining results with appropriate peroxidase conjugation of secondary antibodies and DAB staining

• Sections should be deparaffinized, rehydrated, and subjected to heat-induced epitope retrieval (HIER)

For Western Blotting:

• Cell lysates from HEK-293 cells show clear detection of MID1IP1

• Both transfected and non-transfected cells can be used to demonstrate specificity

• Protein concentration should be carefully quantified for consistent loading

When investigating MID1IP1 expression across different tissues, researchers should note its variable expression pattern, with notable presence in tissues that synthesize triglycerides .

What factors might contribute to non-specific binding when using MID1IP1 Antibody, FITC conjugated?

Several factors can lead to non-specific binding and false-positive results:

• Suboptimal antibody purification:

  • Lower-quality antibody preparations may contain contaminants

  • High-quality antibodies undergo rigorous purification processes (e.g., Protein G purification with >95% purity)

  • Antigen affinity purification methods significantly improve specificity

• Improper blocking:

  • Insufficient blocking can lead to high background

  • Optimize blocking buffer composition (typically 1-5% BSA or serum)

  • Extend blocking time if background persists

• Cross-reactivity issues:

  • The antibody may recognize epitopes on proteins with similar sequences

  • Verify antibody specificity through knockout/knockdown validation studies

  • Consider pre-absorption with relevant antigens if cross-reactivity is suspected

• FITC conjugation ratio:

  • Over-labeling with FITC can alter antibody binding properties

  • Optimal fluorescein/protein (F/P) ratio is critical for specificity

  • Separation of optimally labeled antibodies from under- and over-labeled proteins improves results

How can researchers minimize photobleaching of FITC during microscopy and image acquisition?

FITC is susceptible to photobleaching, which can compromise experimental results. To minimize this effect:

• Sample preparation considerations:

  • Use anti-fade mounting media containing agents like DABCO or ProLong Gold

  • Keep samples in the dark when not actively imaging

  • Prepare samples immediately before imaging when possible

• Microscopy settings optimization:

  • Reduce excitation light intensity to the minimum needed for adequate signal

  • Minimize exposure time during image acquisition

  • Use neutral density filters to attenuate excitation light

  • Employ confocal microscopy with pinhole settings that maximize signal-to-noise ratio

• Acquisition strategies:

  • Capture FITC images first in multi-channel experiments

  • Use frame averaging rather than increasing excitation intensity

  • Implement deconvolution algorithms to enhance signal from lower-intensity images

  • Consider time-lapse intervals carefully to reduce cumulative exposure

By implementing these strategies, researchers can obtain reliable fluorescence data while preserving signal intensity throughout their imaging sessions.

Why might MID1IP1 appear at different molecular weights in Western blot experiments?

MID1IP1 has a calculated molecular weight of approximately 20 kDa, but researchers frequently observe bands at different molecular weights:

• Common observed patterns:

  • 23 kDa band: Slightly higher than predicted weight due to post-translational modifications

  • 46 kDa band: Potentially representing homodimers of MID1IP1

• Factors affecting observed molecular weight:

  • Post-translational modifications (phosphorylation, glycosylation)

  • Formation of protein complexes that resist denaturation

  • Interaction with other proteins like THRSP or ACACA

• Experimental validation approaches:

  • Compare transfected versus non-transfected cell lysates to confirm specificity

  • Use reducing vs. non-reducing conditions to evaluate dimer formation

  • Perform knockout/knockdown studies to verify band identity

  • Consider analyzing both nuclear and cytoplasmic fractions as MID1IP1 localizes to both compartments

When comparing experimental results with literature, researchers should note both the predicted molecular weight (20 kDa) and commonly observed variations (23 kDa, 46 kDa) to properly interpret their Western blot data .

How can MID1IP1 Antibody, FITC conjugated be used in co-localization studies with other proteins?

Co-localization studies provide valuable insights into protein-protein interactions and spatial relationships within cells:

• Experimental design for co-localization:

  • Combine FITC-conjugated MID1IP1 antibody with antibodies against potential interaction partners (e.g., THRSP, ACACA) labeled with spectrally distinct fluorophores

  • Use double immunofluorescence staining with primary antibodies from different host species

  • Select fluorophores with minimal spectral overlap (e.g., FITC + Cy3 or FITC + Alexa 647)

• Technical considerations:

  • Optimize fixation methods to preserve protein-protein interactions

  • Consider proximity ligation assays (PLA) for quantitative assessment of close interactions

  • Implement super-resolution microscopy techniques for detailed co-localization analysis

• Relevant interaction partners:

  • THRSP (Thyroid hormone-responsive protein): MID1IP1 may form homodimers in the absence of THRSP

  • ACACA (Acetyl-CoA carboxylase): MID1IP1 modulates lipogenesis by potentially preventing its interaction with ACACA

  • Transcription factors: As MID1IP1 may function as a transcriptional coactivator

Co-localization studies would be particularly valuable in investigating MID1IP1's role in lipogenesis and transcriptional regulation, providing insights into its mechanistic actions within different cellular compartments.

What approaches can be used to study MID1IP1 expression changes in different disease models?

Investigating MID1IP1 expression in disease contexts requires multiple complementary approaches:

• Cancer research applications:

  • MID1IP1 shows differential expression across cancer types

  • Particularly relevant in solid tumors, hematopoietic/lymphoid malignancies, esophageal/stomach cancers, and acute myeloid leukemia

  • Immunohistochemistry can reveal expression patterns in clinical samples

• Metabolic disease models:

  • Given MID1IP1's role in lipogenesis and triglyceride biosynthesis

  • Quantitative approaches combining Western blot, qPCR, and immunofluorescence provide comprehensive expression data

  • Animal models of obesity, diabetes, or fatty liver disease are particularly relevant

• Experimental methodologies:

  • RNA interference or CRISPR-based approaches to modulate MID1IP1 expression

  • Flow cytometry with FITC-conjugated MID1IP1 antibody to quantify expression levels at single-cell resolution

  • Tissue microarrays to assess expression across multiple patient samples simultaneously

Recent publications highlight the relevance of MID1IP1 in colorectal cancer, where inhibition of CNOT2 induces apoptosis via MID1IP1, and acetylcorynoline induces apoptosis and G2/M phase arrest through the c-Myc signaling pathway .

How can researchers integrate MID1IP1 antibody studies with functional genomics approaches?

Combining antibody-based studies with functional genomics creates powerful research workflows:

• Integration with CRISPR screening:

  • Use genome-wide or targeted CRISPR screens to identify genes that modulate MID1IP1 expression or function

  • Follow with antibody-based validation using FITC-conjugated MID1IP1 antibody

  • Quantify effects through flow cytometry or high-content imaging

• Multi-omics approaches:

  • Correlate protein-level measurements (via antibody-based techniques) with:

    • Transcriptomic data (RNA-seq)

    • Epigenomic profiles (ChIP-seq)

    • Metabolomic measurements (especially lipid profiles)

  • This integration provides insights into regulatory mechanisms

• Pathway analysis frameworks:

  • Place MID1IP1 within broader signaling and metabolic networks

  • Investigate connections to c-Myc signaling, as suggested by recent studies

  • Examine relationships with lipogenic pathways

  • Study interactions with THRSP in triglyceride biosynthesis

• Clinical correlations:

  • Leverage datasets like DepMap to connect MID1IP1 expression with cancer dependencies

  • Correlate expression patterns with patient outcomes or therapeutic responses

  • Identify potential biomarker applications

Through these integrated approaches, researchers can develop comprehensive models of MID1IP1 function in normal physiology and disease states, potentially revealing new therapeutic targets or diagnostic markers.

What emerging technologies might enhance MID1IP1 detection and functional analysis?

Several cutting-edge technologies show promise for advancing MID1IP1 research:

• Advanced imaging approaches:

  • Super-resolution microscopy to visualize subcellular localization with nanometer precision

  • Live-cell imaging with photoactivatable fluorescent proteins to track dynamic behaviors

  • Correlative light and electron microscopy (CLEM) to connect fluorescence data with ultrastructural context

• Single-cell analysis technologies:

  • Single-cell Western blotting to measure MID1IP1 levels in individual cells

  • Mass cytometry (CyTOF) combining MID1IP1 antibodies with metal tags for high-parameter analysis

  • Single-cell RNA-seq paired with protein detection for integrated expression analysis

• Proximity-based interactome mapping:

  • BioID or APEX2 proximity labeling fused to MID1IP1 to identify interaction partners

  • FRET-based assays using FITC-conjugated antibodies to detect protein-protein interactions

  • Mass spectrometry-based approaches to comprehensively map the MID1IP1 interactome

These technologies can provide unprecedented insights into MID1IP1 function, regulation, and potential roles in disease processes.

How might understanding MID1IP1 contribute to therapeutic development in metabolic disorders?

Given MID1IP1's roles in lipogenesis and metabolic regulation, research in this area could have significant therapeutic implications:

• Potential therapeutic applications:

  • Targeting MID1IP1-ACACA interactions to modulate lipid synthesis in metabolic disorders

  • Exploring connections between MID1IP1 and THRSP in lipid metabolism regulation

  • Investigating MID1IP1's role in cancer metabolism, particularly in lipid-dependent tumors

• Model systems for therapeutic development:

  • Cell-based assays using FITC-conjugated MID1IP1 antibodies to screen compound libraries

  • Animal models with altered MID1IP1 expression to evaluate metabolic phenotypes

  • Patient-derived organoids to assess clinical relevance of MID1IP1 modulation

• Biomarker potential:

  • Evaluating MID1IP1 expression levels as indicators of metabolic disease progression

  • Monitoring changes in response to therapeutic interventions

  • Correlating with clinical outcomes in conditions like fatty liver disease or cancer

Future research integrating MID1IP1 antibody-based studies with metabolic profiling could reveal novel intervention points for disorders characterized by dysregulated lipid metabolism.