PRC1 Antibody

What is PRC1 and what are its primary cellular functions?

PRC1 (Protein Regulator of Cytokinesis 1) is a key regulator of cytokinesis that cross-links antiparallel microtubules at an average distance of 35 nM. It plays an essential role in controlling the spatiotemporal formation of the midzone and successful cytokinesis. PRC1 is required for KIF14 localization to the central spindle and midbody, and for recruiting PLK1 to the spindle. It stimulates PLK1 phosphorylation of RACGAP1 to allow recruitment of ECT2 to the central spindle . Additionally, PRC1 demonstrates dynamic temporal and spatial localization throughout the cell cycle - it is located in the nucleus during interphase, becomes associated with mitotic spindles during mitosis, and localizes to the cell mid-body during cytokinesis. The protein is present at high levels during the S and G2/M phases of mitosis, but its levels drop dramatically when the cell exits mitosis and enters the G1 phase . Beyond cytokinesis, PRC1 has also been implicated in cancer pathogenesis, functioning as an oncogene in several cancer types by promoting cell proliferation and inhibiting apoptosis .

What types of PRC1 antibodies are available for research applications?

There are several well-characterized monoclonal antibodies available for PRC1 detection, including but not limited to:

• Clone 16F2 (available as ab119338 and MA1-846) - A mouse monoclonal antibody raised against recombinant full-length protein corresponding to human PRC1

• 67027-1-Ig - A mouse monoclonal IgG1 antibody that targets PRC1 and shows reactivity with human, mouse, and rat samples

These antibodies have been validated for multiple applications including Western Blot (WB), Immunocytochemistry/Immunofluorescence (ICC/IF), and Immunoprecipitation (IP). The recommended dilutions vary by application and specific antibody, as shown in the table below:

Note that optimal dilutions may be sample-dependent and should be determined empirically for each experimental system .

How can I distinguish between PRC1 (Protein Regulator of Cytokinesis 1) and PRC1 (Polycomb Repressive Complex 1) in my research?

This is a critical distinction in research as both use the acronym "PRC1" but refer to different biological entities. When designing experiments or interpreting results:

• Context clarification: Always specify "Protein Regulator of Cytokinesis 1" or "Polycomb Repressive Complex 1" in your methods section

• Molecular weight verification: Protein Regulator of Cytokinesis 1 has a calculated molecular weight of 72 kDa (observed at 66-72 kDa in Western blots) , while Polycomb Repressive Complex 1 components have different molecular weights

• Antibody selection: Ensure antibodies specifically target your protein of interest by checking the immunogen information and validation data

• Co-localization studies: Polycomb Repressive Complex 1 typically localizes to chromatin, while Protein Regulator of Cytokinesis 1 shows dynamic localization during the cell cycle

When publishing, use clear terminology throughout to avoid confusion in the scientific literature.

What are the optimal fixation and permeabilization conditions for PRC1 immunofluorescence staining?

For optimal PRC1 immunofluorescence staining, the following protocol has been validated:

• Fixation: 4% paraformaldehyde provides good preservation of PRC1 antigens while maintaining cellular architecture

• Permeabilization: 0.1% Triton X-100 is effective for allowing antibody access while preserving cellular structures

• Blocking: Standard blocking solutions containing BSA or serum should be applied before antibody incubation

• Antibody dilution: For clone 16F2, dilutions ranging from 1:20 to 1:100 have been successfully used

• Incubation conditions: Overnight incubation at 4°C provides optimal staining with minimal background

For visualization, secondary antibodies conjugated to fluorophores like DyLight-488 have shown good results. Co-staining with F-actin (using Phalloidin) and nuclear staining (using DAPI) can provide valuable contextual information about PRC1 localization during different cell cycle phases .

How can I validate PRC1 antibody specificity in my experimental system?

Rigorous antibody validation is crucial for reliable research outcomes. For PRC1 antibodies, consider implementing these validation strategies:

• Positive controls: Use cell lines known to express PRC1, such as HeLa, MCF-7, HEK-293, A549, or HepG2 cells, which have been verified to show positive signals

• Negative controls: Include samples without primary antibody to assess background and non-specific binding of secondary antibodies

• siRNA knockdown: Deploy PRC1-specific siRNA to reduce expression, which should result in corresponding reduction of antibody signal

• Recombinant protein competition: Pre-incubate the antibody with purified recombinant PRC1 protein before application to samples, which should diminish specific staining

• Western blot verification: Confirm detection of a single band at the expected molecular weight (66-72 kDa)

• Multiple antibody comparison: Use at least two different antibodies targeting distinct epitopes of PRC1 to confirm consistent localization patterns

These validation steps should be documented to support the specificity of your findings.

What cell lines and tissue samples are most appropriate for studying PRC1 expression and function?

Based on validated research, the following experimental systems have proven suitable for PRC1 studies:

Cell Lines with Verified PRC1 Detection:

• Human: HeLa, MCF-7, HEK-293, A549, HepG2, K-562, Raji, U251, A2058

• Rodent: HSC-T6, 4T1

Tissue Samples:

• Human breast cancer tissue

• Human lung cancer tissue

• Liver hepatocellular carcinoma (LIHC) samples

When selecting experimental systems, consider:

• The specific cellular process you're investigating (cytokinesis, cancer proliferation, gene regulation)

• The need for cell cycle synchronization to observe PRC1's dynamic localization

• Whether the species origin matches your antibody's validated reactivity (human, mouse, rat)

• The relevance to your disease model, as PRC1 overexpression has been specifically documented in liver cancer

For studying PRC1's role in cytokinesis, cell lines with good mitotic indices and easy visualization of mitotic structures (like HeLa) are particularly valuable.

How do I design experiments to study PRC1's role in cancer progression and immune regulation?

When investigating PRC1's oncogenic functions and immune regulatory roles, consider this comprehensive experimental approach:

Cancer Progression Studies:

• Expression analysis: Compare PRC1 levels between tumor and adjacent normal tissues using immunohistochemistry and Western blotting

• Prognostic correlation: Analyze survival data in relation to PRC1 expression levels in patient cohorts

• Functional assays: Perform PRC1 knockdown/overexpression followed by:

  • Proliferation assays (MTT, BrdU incorporation)

  • Apoptosis assessment (Annexin V staining, caspase activity)

  • Cell cycle analysis (flow cytometry, EdU incorporation)

  • Migration and invasion assays (transwell, wound healing)

Immune Regulation Investigation:
Research has demonstrated that PRC1 expression correlates with immune cell infiltration in liver cancer. Design experiments to explore this relationship:

• Correlation analysis: Assess PRC1 expression in relation to immune cell markers using:

  • CIBERSORT, QUANTISEQ, and TIDE algorithms on bulk tumor sequencing data

  • Flow cytometry or multiplex immunohistochemistry on tissue samples

• Co-culture experiments: Establish tumor cell-immune cell co-cultures with PRC1-manipulated cancer cells to observe:

  • T regulatory cell (Treg) and myeloid-derived suppressor cell (MDSC) recruitment and activation

  • Effects on CD8+ T cell and B cell responses

• Checkpoint molecule assessment: Analyze correlation between PRC1 expression and immune checkpoint molecules through:

  • mRNA expression correlation analysis

  • Protein co-expression in tissue samples

  • Functional studies with checkpoint inhibitors in PRC1-manipulated models

Research has shown PRC1 overexpression correlates with increased infiltration of immunosuppressive cells (Tregs, PMN-MDSCs) and decreased presence of effector immune cells (B cells, CD8+ T cells) in liver cancer, suggesting PRC1 may contribute to an immunosuppressive tumor microenvironment .

What strategies can I use to differentiate between PRC1's cytokinesis function and its potential role in gene regulation?

PRC1 has distinct roles in cytokinesis and potentially in gene regulation as part of polycomb complexes. To differentiate these functions:

Experimental Approach for Function Separation:

• Domain-specific mutations: Generate constructs with mutations in specific functional domains of PRC1:

  • Microtubule-binding domain mutations to disrupt cytokinesis function

  • Protein-interaction domains that might be involved in polycomb complex formation

• Temporal analysis: Exploit PRC1's cell cycle-dependent expression:

  • Synchronized cell populations at different cell cycle phases

  • ChIP-seq for PRC1 at different cell cycle stages to identify consistent chromatin binding independent of cytokinesis

• Co-immunoprecipitation studies: Identify binding partners:

  • Pull-down of PRC1 followed by mass spectrometry to identify cytokinesis vs. polycomb-related interactors

  • Verification of interactions with known components of cytokinesis machinery vs. polycomb complex members

• Subcellular localization: Use high-resolution microscopy:

  • Immunofluorescence co-staining with markers for:

    • Cytokinesis (e.g., Aurora B, MKLP1)

    • Chromatin repression (e.g., H3K27me3, other polycomb components)

• Transcriptional analysis: After PRC1 manipulation:

  • RNA-seq to identify altered gene expression

  • ChIP-seq to detect PRC1 binding sites at regulated genes

  • Correlation with polycomb-regulated genes and H2AK119ub1 marks

This experimental framework allows for distinguishing between PRC1's structural role in cell division and any potential function in gene regulation.

How can I investigate PRC1's interaction with the microtubule network during different phases of mitosis?

To comprehensively investigate PRC1's dynamic interaction with microtubules throughout mitosis:

Live Cell Imaging Approaches:

• Fluorescent protein tagging: Generate stable cell lines expressing PRC1-GFP/mCherry fusion proteins for real-time visualization

• Photobleaching experiments: Perform FRAP (Fluorescence Recovery After Photobleaching) on PRC1-labeled structures to assess dynamics and turnover rates

• Super-resolution microscopy: Use STORM, PALM, or SIM to visualize PRC1-microtubule interactions at nanometer resolution

Biochemical Characterization:

• Co-sedimentation assays: Mix purified PRC1 with polymerized microtubules and analyze binding through ultracentrifugation

• Surface plasmon resonance: Determine binding kinetics between PRC1 and tubulin/microtubules

• Phosphorylation analysis: Examine how CDK-mediated phosphorylation affects PRC1-microtubule interactions at different mitotic phases

Structural Analysis:

• Electron microscopy: Visualize PRC1-mediated microtubule bundling and cross-linking

• Cryo-EM: Determine the molecular structure of PRC1-microtubule complexes

Functional Perturbation:

• Optogenetics: Use light-inducible PRC1 recruitment/dissociation to assess acute effects on microtubule organization

• Cell cycle-specific degradation: Employ an auxin-inducible degron system to remove PRC1 at specific mitotic phases

• Microtubule drug combination: Couple PRC1 manipulation with microtubule-stabilizing (taxol) or destabilizing (nocodazole) drugs at varying concentrations

Understanding these interactions may provide insights into how PRC1 ensures correct spindle midzone formation and serves as a marker for the cleavage furrow .

How should I troubleshoot weak or inconsistent PRC1 antibody signals in Western blotting?

When encountering weak or inconsistent PRC1 signals in Western blotting, systematically address these potential issues:

Sample Preparation:

• Cell cycle consideration: PRC1 levels fluctuate dramatically throughout the cell cycle, with highest expression in S and G2/M phases and lowest in G1 phase. Consider synchronizing cells or using asynchronous populations with high mitotic indices

• Protein extraction: Use RIPA buffer with protease inhibitors. For complete extraction, include brief sonication steps

• Sample handling: Minimize freeze-thaw cycles and maintain samples at appropriate temperatures to prevent degradation

Blotting Protocol Optimization:

• Antibody dilution: For the 67027-1-Ig antibody, test a range between 1:2000-1:10000

• Incubation time: Extend primary antibody incubation to overnight at 4°C

• Blocking optimization: Test different blocking agents (5% milk, 5% BSA) for reduced background

• Enhanced detection: Consider using high-sensitivity ECL substrates for detection

• Transfer efficiency: Optimize transfer conditions (time, voltage, buffer composition) for high molecular weight proteins (~72 kDa)

Controls and Validation:

• Positive control: Include lysates from cells known to express PRC1 (HeLa, MCF-7, HEK-293, A549, HepG2)

• Loading control: Verify equal loading with housekeeping proteins that don't fluctuate with cell cycle

• Expected band size: Confirm detection at the expected molecular weight (66-72 kDa)

Antibody-Specific Considerations:
If persistent issues occur with one antibody clone, consider testing an alternative PRC1 antibody targeting a different epitope to rule out antibody-specific limitations.

What variables need to be controlled when quantifying PRC1 expression in tumor samples?

Accurate quantification of PRC1 expression in tumor samples requires controlling for several variables that could confound results:

Tissue Processing Variables:

• Fixation protocol: Standardize fixation time and conditions, as overfixation may mask epitopes

• Antigen retrieval: Optimize antigen retrieval methods (suggested: TE buffer pH 9.0 or citrate buffer pH 6.0)

• Storage conditions: Account for tissue age and storage conditions that might affect antigen preservation

Biological Variables:

• Cell cycle heterogeneity: PRC1 expression varies throughout the cell cycle, so assess proliferation markers in parallel

• Tumor heterogeneity: Analyze multiple regions within a tumor to account for spatial heterogeneity

• Tumor type and grade: Compare similar histological subtypes and grades across samples

• Stromal content: Normalize for epithelial vs. stromal content, as PRC1 may be differentially expressed

Technical Variables:

• Antibody validation: Confirm specificity in tumor tissue with appropriate controls

• Quantification method: Standardize scoring systems:

  • For IHC: Use digital image analysis with standardized algorithms

  • For Western blot: Normalize to consistent housekeeping proteins

  • For RT-qPCR: Use multiple reference genes for normalization

• Batch effects: Process samples in randomized batches and include common control samples across batches

Reporting Standards:

• Document detailed methodological parameters

• Report both raw and normalized data

• Include representative images showing the range of expression patterns

Research has shown PRC1 overexpression in liver hepatocellular carcinoma correlates with progressed clinical stage and poor prognosis, making standardized quantification crucial for clinical correlation studies .

How can I differentiate between specific and non-specific staining patterns when using PRC1 antibodies for immunofluorescence?

Distinguishing specific from non-specific staining requires systematic controls and pattern recognition:

Control Experiments:

• Primary antibody omission: Include samples processed identically but without primary antibody to identify secondary antibody non-specific binding

• Blocking peptide competition: Pre-incubate antibody with excess PRC1 recombinant protein to confirm specificity

• PRC1 knockdown/knockout: Use siRNA or CRISPR to reduce PRC1 expression and confirm corresponding reduction in signal

• Multiple antibodies: Validate staining pattern with different PRC1 antibodies targeting distinct epitopes

Pattern Analysis:

• Cell cycle-dependent localization: Authentic PRC1 staining should show characteristic patterns:

  • Nuclear localization during interphase

  • Mitotic spindle association during mitosis

  • Midbody localization during cytokinesis

• Co-localization studies: PRC1 should co-localize with:

  • Spindle microtubules during metaphase and anaphase

  • Centralspindlin complex components at the midbody

• Signal distribution: Non-specific staining often appears as:

  • Uniform cytoplasmic signal

  • Irregular aggregates

  • Persistent staining in knockdown controls

Imaging Considerations:

• Multi-channel acquisition: Always image PRC1 alongside F-actin (Phalloidin) and nuclear (DAPI) markers to provide contextual localization

• Exposure settings: Use identical acquisition parameters across samples and controls

• Resolution requirements: Employ appropriate magnification (60X recommended) to resolve subcellular structures

Published immunofluorescence images show specific PRC1 staining in multiple cell lines (HeLa, U251, A2058) with characteristic cell cycle-dependent patterns, providing reference for expected authentic staining .

How can I investigate the relationship between PRC1 expression and immune checkpoint molecules in cancer?

Recent research has revealed potential connections between PRC1 and immune checkpoint regulation, particularly in liver cancer. To investigate these relationships:

Correlation Analysis Approach:

• Transcriptomic analysis: Perform correlation analysis between PRC1 expression and immune checkpoint genes in:

  • Public databases (TCGA, GEO) using tools like TIMER

  • Patient cohorts using RNA-seq or NanoString panels

• Protein co-expression: Use multiplex immunohistochemistry or immunofluorescence to assess simultaneous expression of PRC1 and checkpoint molecules in tissue sections

• Single-cell analysis: Apply scRNA-seq to identify cell populations co-expressing PRC1 and checkpoint molecules

Functional Investigation:

• PRC1 manipulation: Use genetic approaches (knockdown, overexpression, CRISPR) to modulate PRC1 levels in cancer cells, then assess:

  • Changes in checkpoint molecule expression at mRNA and protein levels

  • Alterations in immune cell co-culture responses

  • Effects on checkpoint blockade therapy in animal models

• Signaling pathway analysis: Investigate common regulatory pathways between PRC1 and checkpoint molecules through:

  • Pathway inhibition experiments

  • Phosphoproteomic analysis

  • Transcription factor binding site analysis

Clinical Correlation:

• Response to immunotherapy: Stratify patient cohorts by PRC1 expression levels and correlate with response to checkpoint inhibitor therapy

• Prognostic significance: Develop combined PRC1/checkpoint molecule expression signatures for outcome prediction

Research has shown PRC1 is positively correlated with the expression of tumor immune checkpoint molecules in liver cancer, suggesting it may contribute to the immunosuppressive microenvironment through multiple mechanisms .

What are the most effective approaches to study PRC1's role in chromatin regulation during DNA replication?

To investigate PRC1's function in chromatin regulation during DNA replication, particularly focusing on the PCGF1-PRC1 variant complex:

Chromatin Analysis Techniques:

• Nascent chromatin capture: Use techniques like iPOND (isolation of Proteins On Nascent DNA) or NCC (Nascent Chromatin Capture) coupled with mass spectrometry to identify PRC1 components at replication forks

• ChIP-seq during S phase: Perform chromatin immunoprecipitation sequencing for PRC1 components in synchronized cells progressing through S phase

• DRIP-seq: DNA-RNA Immunoprecipitation sequencing to assess R-loop formation at replication forks in the presence/absence of PRC1

Functional Approaches:

• Genetic manipulation: Generate conditional knockout/knockdown of specific PRC1 components (particularly PCGF1) in cellular models like hematopoietic stem and progenitor cells (HSPCs)

• Nucleosome assembly assays: Monitor nucleosome deposition on newly replicated DNA with and without functional PRC1 complexes

• Replication stress induction: Assess how PRC1 depletion affects cellular responses to replication stress using DNA damaging agents

Molecular Readouts:

• Histone modification analysis: Track histone marks associated with PRC1 function (particularly H2AK119ub1) on nascent chromatin

• Chromatin accessibility: Measure changes in chromatin accessibility at replication forks using ATAC-seq in PRC1-deficient cells

• Replication timing analysis: Assess changes in replication timing domains upon PRC1 manipulation

Research has demonstrated that PCGF1-PRC1 prevents overloading of activators and chromatin remodeling factors on nascent DNA, mediating proper nucleosome deposition and downstream chromatin configurations in hematopoietic stem and progenitor cells .

How can researchers integrate multi-omics approaches to understand PRC1's diverse roles in cellular processes?

To comprehensively understand PRC1's multifaceted functions across cytokinesis, gene regulation, and cancer progression, integrate these multi-omics approaches:

Integrated Experimental Design:

• Unified cellular models: Establish consistent cell systems where PRC1 can be manipulated (knockdown, overexpression, mutation) for parallel multi-omics analyses

• Temporal resolution: Capture dynamic changes by analyzing synchronized cells at defined cell cycle stages

• Spatial compartmentalization: Separate analyses of nuclear, cytoplasmic, and chromatin-bound fractions

Multi-omics Data Generation:

• Genomics/Epigenomics:

  • ChIP-seq for PRC1 binding sites and histone modifications (H2AK119ub1)

  • ATAC-seq for chromatin accessibility changes

  • Hi-C for 3D genome organization

• Transcriptomics:

  • RNA-seq for expression changes

  • NET-seq for nascent transcription analysis

  • scRNA-seq for cell population heterogeneity

• Proteomics/Interactomics:

  • BioID or proximity labeling to identify context-specific interactors

  • Phosphoproteomics to map PRC1 regulation by CDKs

  • Proteome-wide ubiquitylation profiling

• Functional genomics:

  • CRISPR screens to identify synthetic interactions

  • Genetic suppressor screens to map functional pathways

Computational Integration:

• Multi-modal data integration: Apply machine learning approaches to identify patterns across datasets

• Network analysis: Construct protein-protein and gene regulatory networks centering on PRC1

• Causal inference: Use statistical methods to infer causality between PRC1 perturbation and downstream effects

Validation Strategies:

• Targeted mechanistic studies: Follow up computational predictions with focused molecular experiments

• In vivo models: Validate key findings in appropriate animal models

• Patient sample correlation: Connect multi-omics findings with patient data to establish clinical relevance

This integrated approach would comprehensively capture PRC1's roles in cytokinesis regulation, its function in polycomb-mediated gene repression, and its contribution to cancer pathogenesis and immune modulation .