RUBCN Antibody, FITC conjugated

What is RUBCN and why is it important in autophagy research?

RUBCN (Rubicon) is a protein that functions as a negative regulator of autophagy by inhibiting PIK3C3 activity and negatively regulating PI3K complex II (PI3KC3-C2) function under basal conditions. The human canonical protein has 972 amino acid residues with a molecular mass of 108.6 kDa and is primarily localized in lysosomes . RUBCN is notably expressed in the spleen, fallopian tube, bronchus, and bone marrow . Its importance in autophagy research stems from its role in modulating autophagic activity, which has significant implications for aging processes and various pathological conditions. Studies have shown that RUBCN expression increases with age in worms, flies, and mice, suggesting it may be a key factor in age-dependent impairment of autophagy .

What are the common applications for RUBCN antibodies in research?

RUBCN antibodies are utilized across multiple immunodetection techniques, with Western Blot being the most widely reported application. Other common applications include ELISA, Immunocytochemistry, Immunofluorescence, and Immunohistochemistry . These antibodies are crucial for studying autophagy regulation, aging mechanisms, and pathological conditions where RUBCN may play a role. Over 80 citations in scientific literature describe the use of RUBCN antibodies in research across various fields . Researchers commonly employ these antibodies to investigate the role of RUBCN in disease models, particularly those related to kidney injury, neurodegeneration, and aging.

Why would a researcher choose a FITC-conjugated RUBCN antibody over unconjugated versions?

FITC-conjugated RUBCN antibodies provide direct fluorescent visualization without requiring secondary antibody incubation, which streamlines experimental workflows and reduces background noise in certain applications. Fluorescein is excited by the 488 nm line of an argon laser with emission collected at 530 nm, making it compatible with most standard fluorescence microscopy and flow cytometry equipment . This conjugation is particularly valuable for flow cytometry, direct immunofluorescence microscopy, and multiplex staining where different fluorophores can be used simultaneously to detect multiple targets. The direct conjugation also eliminates potential cross-reactivity issues that can occur with secondary antibodies, especially in co-staining experiments involving multiple primary antibodies from the same species.

What is the optimal protocol for FITC conjugation of RUBCN antibodies?

When conjugating FITC to RUBCN antibodies, the following methodological approach is recommended:

• Antibody preparation: Ensure the antibody is at a concentration of at least 2 mg/ml in a buffer free of primary amines (avoid Tris-based buffers) .

• Conjugation ratio determination: Perform parallel conjugations with different FITC-to-antibody ratios. Typically, 3-6 FITC molecules per antibody yield optimal results. Higher conjugations can cause solubility problems and internal quenching .

• Conjugation reaction: Dissolve FITC in anhydrous DMSO immediately before use (as it is unstable once solubilized) and add to the antibody solution in a carbonate buffer (pH 9.0-9.5) .

• Purification: Separate conjugated antibody from free FITC using size exclusion chromatography.

• Characterization: Determine the fluorophore-to-protein ratio by measuring absorbance at 280 nm (protein) and 495 nm (FITC) and calculate using the formula:
  $\frac{Moles\ FITC}{Moles\ protein} = \frac{A_{495} \times Dilution\ factor}{68,000 \times Protein\ concentration (M)}$

• Optimization validation: Test different conjugates for brightness and background staining to select the optimal preparation .

Note that the extent of FITC conjugation may depend on antibody concentration, so maintain consistent concentrations for reproducible results.

How should researchers validate the specificity of FITC-conjugated RUBCN antibodies?

Validation of FITC-conjugated RUBCN antibodies should employ multiple complementary approaches:

• Knockout/knockdown controls: Test the antibody in RUBCN-deficient systems, such as RUBCN knockout mice or cells treated with RUBCN siRNA/shRNA . The absence of signal in these systems confirms specificity.

• Overexpression systems: Test in cells overexpressing tagged RUBCN and verify co-localization of antibody signal with the tag.

• Western blot correlation: Perform parallel Western blot analysis to confirm that the fluorescence signal corresponds to the expected molecular weight (108.6 kDa) .

• Cross-reactivity assessment: Test the antibody against related proteins, particularly those in the PI3K complex, to ensure specificity.

• Blocking peptide competition: Pre-incubate the antibody with a RUBCN-specific peptide to demonstrate signal reduction.

• Subcellular localization: Confirm the expected lysosomal localization pattern using co-staining with established lysosomal markers .

A comprehensive validation should demonstrate consistent results across multiple validation methods, with appropriate positive and negative controls.

What factors affect the performance of FITC-conjugated RUBCN antibodies in flow cytometry?

Several technical factors can significantly impact the performance of FITC-conjugated RUBCN antibodies in flow cytometry:

• Fluorophore-to-protein ratio: The optimal ratio is typically 3-6 FITC molecules per antibody. Higher ratios may cause quenching and reduced brightness, while lower ratios may yield insufficient signal .

• Fixation and permeabilization: Since RUBCN is primarily localized in lysosomes , proper permeabilization is critical. Different fixatives (paraformaldehyde vs. methanol) and permeabilization agents can affect epitope accessibility.

• Autofluorescence: Cellular autofluorescence can interfere with FITC signal, particularly in tissues with high autofluorescence like kidney. Use appropriate controls and consider alternative fluorophores with longer emission wavelengths for such tissues.

• Photobleaching: FITC is prone to photobleaching, so minimize exposure to light during sample preparation.

• pH sensitivity: FITC fluorescence is pH-dependent, with optimal emission at slightly alkaline pH. Ensure consistent buffer pH during experiments.

• Compensation requirements: When using multiple fluorophores, proper compensation is essential as FITC has broad emission that may overlap with other channels.

• Antibody concentration: Titrate the antibody to determine the optimal concentration that provides specific staining with minimal background.

To optimize performance, develop a standardized protocol with appropriate controls and consistent sample preparation conditions.

How can researchers troubleshoot weak or non-specific signals when using FITC-conjugated RUBCN antibodies?

When encountering weak or non-specific signals with FITC-conjugated RUBCN antibodies, systematically address these issues through the following approach:

For weak signals:

• Verify antibody concentration and integrity (check for denaturation or aggregation).

• Optimize fixation and permeabilization protocols to improve antigen accessibility.

• Increase antibody incubation time or temperature.

• Enhance signal using amplification systems compatible with direct conjugates.

• Check FITC conjugation efficiency and consider using antibodies with higher fluorophore-to-protein ratios.

• Ensure RUBCN is sufficiently expressed in your experimental system.

For non-specific signals:

• Include proper blocking steps (e.g., with serum appropriate to your experimental system).

• Titrate antibody concentration to find the optimal signal-to-noise ratio.

• Include appropriate controls (isotype, RUBCN-deficient samples) .

• Validate specificity through Western blot or immunoprecipitation.

• Consider potential crossreactivity with RUBCN isoforms (up to 3 different isoforms have been reported) .

• Filter samples to remove cell aggregates or debris.

If problems persist, compare the performance of different RUBCN antibody clones or consider alternative detection methods like using unconjugated primary antibodies with fluorescent secondary antibodies.

How can FITC-conjugated RUBCN antibodies be used to investigate autophagy flux in live cells?

Investigating autophagy flux with FITC-conjugated RUBCN antibodies requires specific methodological approaches:

• Cell permeabilization strategy: Use gentle permeabilization techniques like digitonin that maintain cellular architecture while allowing antibody entry. This approach is preferable to traditional fixation for certain dynamic studies.

• Live-cell compatible delivery methods: Consider protein transfection methods to deliver FITC-conjugated RUBCN antibodies into live cells, such as:

  • Cell-penetrating peptide conjugation

  • Electroporation with optimized parameters

  • Microinjection for single-cell analysis

• Dual reporter systems: Combine FITC-RUBCN antibody staining with autophagy reporters like GFP-LC3 or RFP-LC3 to correlate RUBCN localization with autophagosome formation and clearance .

• Time-lapse imaging: Establish protocols for time-lapse microscopy to track RUBCN dynamics in relation to autophagy flux, using Bafilomycin A (BafA) as a flux inhibitor at specific timepoints .

• Quantification methods: Implement automated image analysis to quantify:

  • Colocalization of RUBCN with autophagy markers

  • Changes in RUBCN distribution during autophagy modulation

  • Correlation between RUBCN levels and autophagosome/autolysosome numbers

In C. elegans models, researchers have successfully combined RUBCN knockdown with BafA treatment to assess autophagy flux, demonstrating that this approach can provide valuable insights into RUBCN's role in regulating autophagy .

How does RUBCN expression change with age, and how can FITC-conjugated antibodies help investigate this phenomenon?

RUBCN expression significantly increases with age in multiple model organisms, including worms, flies, and mice at both transcript and protein levels, making it a potential biomarker of aging . FITC-conjugated RUBCN antibodies can be instrumental in investigating this age-dependent expression pattern through:

• Quantitative tissue analysis: Flow cytometry with FITC-RUBCN antibodies allows precise quantification of RUBCN protein levels across different age groups and tissues. This approach has revealed that RUBCN increases in multiple tissues with age, with tissue-specific patterns of accumulation .

• Spatial distribution mapping: Immunofluorescence microscopy using FITC-RUBCN antibodies can map the spatial distribution of RUBCN in aged tissues, revealing how its subcellular localization may change over time.

• Multi-parametric analysis: FITC-RUBCN antibodies can be combined with other fluorescent markers in flow cytometry or microscopy to correlate RUBCN levels with:

  • Markers of cellular senescence

  • Autophagy activity indicators

  • Tissue-specific damage markers

• Intervention studies: Track changes in RUBCN expression following interventions that extend lifespan, such as caloric restriction. Research has shown that RUBCN is suppressed in several long-lived mutant worms and calorie-restricted mice .

• Neural tissue analysis: Studies indicate that RUBCN knockdown in neurons has the greatest effect on lifespan , suggesting tissue-specific analysis of neuronal RUBCN levels with age is particularly valuable.

This approach can help establish RUBCN as a molecular marker of aging and identify potential interventions that target RUBCN to promote healthy aging.

How can researchers use FITC-conjugated RUBCN antibodies to study the role of RUBCN in kidney injury models?

FITC-conjugated RUBCN antibodies offer valuable approaches for investigating RUBCN's role in kidney injury, particularly given that RUBCN-deficient mice show hypersensitivity to acute kidney injury (AKI) :

• Flow cytometry analysis of kidney cells:

  • Isolate kidney cells from models of ischemia-reperfusion injury (IRI) or cisplatin-induced AKI

  • Use FITC-RUBCN antibodies to quantify RUBCN expression in specific kidney cell populations

  • Correlate RUBCN levels with injury markers and necroptosis indicators

• Multiplex immunofluorescence microscopy:

  • Combine FITC-RUBCN antibodies with markers for:

    • Tubular injury (KIM-1, NGAL)

    • Necroptosis (phospho-MLKL)

    • Pyroptosis (GSDMD)

  • This allows spatial correlation between RUBCN expression and specific injury processes

• Time-course analysis:

  • Monitor RUBCN expression changes at different timepoints following kidney injury

  • Correlate with progression of renal pathology and functional decline

• Mechanistic studies:

  • In RUBCN/MLKL double knockout models, use FITC-RUBCN antibodies to verify absence of RUBCN while studying how MLKL deletion partially reverses AKI sensitivity

  • Investigate the relationship between RUBCN and necroptotic pathway components

• Chronic kidney disease (CKD) investigation:

  • Use FITC-RUBCN antibodies to study RUBCN expression in aged mice that develop CKD

  • Correlate RUBCN levels with interstitial fibrosis severity

This methodology allows researchers to elucidate the mechanisms by which RUBCN influences kidney injury susceptibility and progression to chronic kidney disease.

How do the detection characteristics of FITC-conjugated RUBCN antibodies compare with other fluorophore conjugates?

When selecting fluorophore conjugates for RUBCN detection, researchers should consider these comparative characteristics:

When comparing detection methods, FITC-RUBCN antibodies typically show lower sensitivity than enzyme-linked detection (e.g., HRP) for Western blotting but offer superior spatial resolution for microscopy applications and the ability to quantify expression levels in heterogeneous cell populations through flow cytometry.

How should researchers interpret contradictory results between FITC-RUBCN antibody staining and genetic expression data?

When facing discrepancies between FITC-RUBCN antibody staining and genetic expression data, implement this systematic analysis framework:

• Technical validation:

  • Verify antibody specificity using knockout/knockdown controls

  • Confirm primer specificity for qRT-PCR through melt curve analysis and sequencing

  • Ensure RNA integrity through appropriate quality controls

• Post-transcriptional regulation assessment:

  • RUBCN protein levels may not directly correlate with mRNA due to post-transcriptional regulation

  • Measure protein stability and half-life through cycloheximide chase experiments

  • Investigate microRNA regulation of RUBCN expression

• Isoform-specific analysis:

  • Determine whether the antibody detects all RUBCN isoforms (up to 3 have been reported)

  • Design isoform-specific primers to quantify expression of different RUBCN variants

  • Compare results with antibodies targeting different RUBCN epitopes

• Temporal factors:

  • Consider time-lag between transcription and translation

  • Implement time-course experiments to track both mRNA and protein levels

• Subcellular localization consideration:

  • Assess whether changes in RUBCN distribution rather than total expression explain discrepancies

  • Compare whole-cell protein extraction with compartment-specific fractionation

• Methodology comparison table:

  Parameter	FITC-RUBCN Antibody	qRT-PCR
  Detection target	Protein	mRNA
  Sensitivity	Moderate	High
  Spatial information	Yes	No
  Quantitative range	Limited dynamic range	Wide dynamic range
  Isoform distinction	Epitope-dependent	Primer-dependent
  Post-translational modifications	Detected	Not detected

By systematically evaluating these factors, researchers can identify whether discrepancies reflect biological regulation or technical limitations.

How can FITC-conjugated RUBCN antibodies be utilized in the study of neurodegenerative diseases?

FITC-conjugated RUBCN antibodies offer valuable approaches for investigating neurodegenerative conditions, particularly given RUBCN's role in α-synuclein accumulation and autophagy regulation :

• Brain section analysis:

  • Use FITC-RUBCN antibodies in immunofluorescence studies of brain tissue from neurodegenerative disease models

  • Co-stain with markers of protein aggregation (α-synuclein, tau, amyloid-β)

  • Quantify correlation between RUBCN expression and aggregate burden

• Primary neuron culture applications:

  • Apply FITC-RUBCN antibodies to visualize RUBCN distribution in cultured neurons

  • Track changes in response to autophagy modulators

  • Combine with live-cell imaging of autophagy processes

• Neuron-specific RUBCN modulation:

  • Utilize tissue-specific knockdown models, such as Nestin-Cre RUBCN knockout mice

  • Assess RUBCN levels following manipulation using FITC-RUBCN antibodies

  • Correlate with neuropathological outcomes

• FITC-based flow cytometry of brain cells:

  • Isolate neurons and glia from models of neurodegeneration

  • Quantify RUBCN levels in specific cell populations

  • Correlate with markers of neuronal health and autophagy function

• Multiplex imaging protocols:

  • Combine FITC-RUBCN with markers for:

    • Autophagy (LC3, p62)

    • Lysosomes (LAMP1, LAMP2)

    • Cell stress (ubiquitin, HSPs)

  • Create a comprehensive spatial map of RUBCN's relationship to disease processes

This methodological approach can help elucidate how RUBCN contributes to protein aggregation and neurodegeneration, potentially identifying new therapeutic targets for intervention.

What methodological approaches can integrate FITC-conjugated RUBCN antibodies in high-content screening for autophagy modulators?

Integrating FITC-conjugated RUBCN antibodies into high-content screening offers powerful approaches for identifying compounds that modulate autophagy through RUBCN-dependent mechanisms:

• Automated microscopy workflow:

  • Establish cell lines with stable expression of secondary autophagy markers (RFP-LC3, GFP-p62)

  • Develop FITC-RUBCN antibody staining protocols compatible with automated liquid handling

  • Implement nuclear counterstaining for cell segmentation

  • Create analysis pipelines that quantify:

    • RUBCN intensity and subcellular distribution

    • Colocalization with autophagy markers

    • Morphological features of autophagic structures

• Multiparametric readouts:

  • Primary measures: RUBCN intensity, localization, degradation

  • Secondary measures: Autophagosome number/size, autophagic flux (using BafA-treated controls)

  • Tertiary measures: Cell viability, proliferation, morphology

• Validation cascade:

  • Primary screen: FITC-RUBCN antibody for expression/localization changes

  • Confirmation: Orthogonal autophagy assays (Western blot for LC3-II/LC3-I)

  • Mechanism exploration: RUBCN knockout cells to confirm compound specificity

  • Target engagement: In vitro binding assays

• Data analysis algorithms:

  • Machine learning classification of compound effects

  • Time-course analysis for transient vs. sustained effects

  • Multi-parametric similarity scoring to identify compounds with related mechanisms

• Application to disease models:

  • Screen compounds in cells from kidney injury or neurodegeneration models

  • Correlate RUBCN modulation with disease-relevant endpoints

This methodological framework enables identification of compounds that specifically target RUBCN-dependent aspects of autophagy regulation, potentially leading to therapeutic approaches for age-related disorders where RUBCN dysregulation plays a role.