ZNF134 Antibody

What is ZNF134 and why is it significant in biomedical research?

ZNF134 (zinc finger protein, 134) is classified as a Kruppel C2H2-type zinc-finger transcriptional regulator containing 11 C2H2-type zinc finger domains. Its significance in research stems from its role as a DNA-binding transcriptional regulator that impacts HIV-1 pathogenesis. ZNF134 has been identified as a novel positive regulator of HIV-1 that specifically binds to the HIV-1 Long Terminal Repeat (LTR) sequence, promoting LTR-driven transcription and viral production . Additionally, ZNF134 shows notably elevated expression in tuberculosis patients and during mycobacterial infections, suggesting its potential involvement in HIV-TB co-infection dynamics . The protein localizes to the nucleus, consistent with its function as a transcriptional regulator .

What types of ZNF134 antibodies are available for research, and what applications are they validated for?

Commercial ZNF134 antibodies are available in multiple formats with validation for various research applications. Polyclonal rabbit antibodies are commonly used, with validation for Western Blotting (WB), Immunofluorescence (IF), Immunohistochemistry on paraffin-embedded sections (IHC-P), and Immunocytochemistry (ICC) . Mouse monoclonal antibodies (such as clone 2D10) are also available with validation for WB and ELISA applications . These antibodies target different regions of the ZNF134 protein, including the central region, N-terminal domain, and specific amino acid sequences (e.g., AA 105-193, AA 128-177, AA 139-167) . The diversity in available antibodies allows researchers to select reagents optimized for their specific experimental requirements and target epitopes.

How does ZNF134 function at the molecular level?

ZNF134 functions as a nuclear transcription factor containing multiple C2H2-type zinc finger domains. These domains facilitate sequence-specific DNA binding and transcriptional regulation. In the context of HIV-1 infection, ZNF134 binds to the Long Terminal Repeat (LTR) region of the HIV-1 genome and enhances viral transcription . Experimental evidence has demonstrated that ZNF134 overexpression results in approximately 10-fold increase in HIV-1 transcript levels and a 2-fold increase in viral production . Mechanistically, ZNF134 appears to enhance LTR-driven gene expression, potentially by recruiting transcriptional machinery or modifying chromatin structure, although the precise molecular mechanisms require further investigation. The protein contains multiple zinc finger motifs which likely mediate its interaction with nucleic acids in a sequence-specific manner .

What are the optimal conditions for using ZNF134 antibodies in Western blot applications?

For optimal Western blot applications with ZNF134 antibodies, researchers should consider the following methodological approach:

• Sample preparation: Extract proteins under denaturing conditions using RIPA or similar lysis buffers containing protease inhibitors.

• Gel selection: Use 10-12% SDS-PAGE gels, as the predicted molecular weight of human ZNF134 is approximately 73 kDa.

• Transfer conditions: Perform transfer to PVDF membranes (preferred over nitrocellulose for zinc finger proteins) at 100V for 60-90 minutes in standard transfer buffer containing 20% methanol.

• Blocking: Block membranes with 5% non-fat dry milk or BSA in TBST for 1 hour at room temperature.

• Primary antibody incubation: Dilute ZNF134 antibodies to manufacturer-recommended concentrations (typically 1:500-1:2000) in blocking buffer and incubate overnight at 4°C .

• Detection system: HRP-conjugated secondary antibodies with ECL detection systems are generally effective.

• Controls: Include positive controls such as lysates from cells known to express ZNF134 (T-lymphocytes, monocytes, or neural cells) .

These conditions may require optimization depending on the specific antibody and experimental system being used.

How can researchers validate the specificity of ZNF134 antibodies in their experimental system?

Validating ZNF134 antibody specificity requires a multi-faceted approach:

• Knockdown/knockout controls: Utilize siRNA-mediated knockdown of ZNF134 (effective at 50 picomoles concentration) to demonstrate specificity by showing reduced signal intensity compared to scrambled siRNA controls .

• Overexpression validation: Express recombinant ZNF134 (e.g., hZNF-134-GFP fusion protein) in suitable cell lines and confirm detection at the expected molecular weight .

• Immunoprecipitation followed by mass spectrometry: Perform IP with the ZNF134 antibody followed by MS to confirm target identity.

• Cross-reactivity testing: Test the antibody against related zinc finger proteins with similar sequence homology, particularly those with C2H2 zinc finger motifs.

• Peptide competition assay: Pre-incubate the antibody with the immunizing peptide to demonstrate signal reduction in competitive binding.

• Multiple antibody validation: Compare results using antibodies raised against different epitopes of ZNF134 (e.g., antibodies targeting AA 105-193 vs. AA 128-177) .

• Negative control tissues/cells: Include samples known to have very low or absent ZNF134 expression.

Which cell lines and primary cells are most appropriate for studying ZNF134 expression and function?

Based on the available research data, the following cellular models are appropriate for ZNF134 studies:

• Human cell lines:

  • Neural cells: Astrocytoma 1321N1 and Glioblastoma GO-G-CCM show detectable ZNF134 expression and responsiveness to HIV infection .

  • T-lymphocyte lines: Express ZNF134 and are relevant for HIV infection studies .

  • Monocytic lines: Express ZNF134 and are pertinent for TB infection models .

  • HEK293T cells: Demonstrated to express ZNF134 and useful for transfection experiments with good efficiency .

• Primary cells:

  • PBMCs: Peripheral blood mononuclear cells from healthy donors, HIV patients, TB patients, and HIV-TB co-infected patients show differential ZNF134 expression patterns .

  • Primary T cells: Relevant for HIV infection studies.

  • Primary monocytes/macrophages: Important for mycobacterial infection studies.

• Comparative expression profile:
  ZNF134 transcript levels have been detected in multiple HIV-permissive cell types, suggesting it is not neural cell-specific but more broadly expressed across cell types relevant to HIV and TB pathogenesis .

When selecting experimental models, researchers should consider the baseline expression of ZNF134 and the biological question being addressed (HIV pathogenesis, TB infection, or co-infection dynamics).

How can ZNF134 antibodies be used to investigate the role of this protein in HIV-TB co-infection?

Investigating ZNF134's role in HIV-TB co-infection requires sophisticated experimental approaches:

• Comparative expression analysis: Use ZNF134 antibodies for Western blot and immunohistochemistry to quantify protein levels in:

  • Uninfected control cells

  • HIV-infected cells

  • Mycobacteria-infected cells

  • Co-infected cells

• Temporal dynamics assessment: Establish time-course experiments to determine whether ZNF134 upregulation precedes or follows viral replication enhancement.

• Subcellular localization studies: Employ immunofluorescence with ZNF134 antibodies to track protein localization changes during mono-infection versus co-infection scenarios.

• Chromatin immunoprecipitation (ChIP): Use ZNF134 antibodies for ChIP assays to map binding patterns to the HIV-1 LTR and potential mycobacterial-induced host genes.

• Co-immunoprecipitation (Co-IP): Identify interaction partners that differ between HIV mono-infection and co-infection conditions.

• Ex vivo validation: Compare ZNF134 levels in patient-derived samples as research has shown TB patients (n=22) exhibited approximately 40-fold higher ZNF134 transcript levels compared to healthy controls .

• Mechanistic studies: Combine ZNF134 knockdown with infection models to determine whether reduced ZNF134 levels can mitigate the accelerated HIV disease progression typically observed during co-infection.

These approaches would help elucidate whether ZNF134 represents a molecular mechanism explaining mycobacteria-enhanced HIV-1 pathogenesis.

What is known about the epitope specificity of ZNF134 antibodies and potential cross-reactivity with other zinc finger proteins?

Epitope specificity and cross-reactivity considerations for ZNF134 antibodies present important research challenges:

• Epitope mapping: Commercial ZNF134 antibodies target several regions, including:

  • Central region (proprietary sequence)

  • Amino acids 105-193

  • Amino acids 128-177

  • Amino acids 139-167 (N-Terminal)

• Structural considerations: ZNF134 contains 11 C2H2-type zinc finger domains with highly conserved motifs found across the zinc finger protein family .

• Cross-reactivity potential: Significant sequence similarity exists between ZNF134 and other C2H2 zinc finger proteins. For instance, zinc finger proteins ZNF700 and ZNF768 show high sequence similarity (bl2seq score of 262, E-value 1E-81) in their zinc finger motifs .

• Immunogenic regions: The classical C2H2 ZNF motifs have been identified as potential epitopes with elevated immunogenic potential .

• Validation approaches:

  • Peptide competition assays using specific zinc finger motifs

  • Testing against recombinant zinc finger proteins with known sequence homology

  • Western blot analysis in tissues expressing multiple zinc finger proteins

• Predictive analysis: In silico epitope prediction tools can help identify potentially cross-reactive regions based on structural and sequence analysis of the C2H2 domains.

Researchers should carefully select antibodies targeting unique regions of ZNF134 when specific detection is critical to experimental outcomes.

What is the potential role of ZNF134 as a biomarker in HIV/TB diagnosis and how might antibody-based detection methods be optimized for this purpose?

The potential of ZNF134 as a biomarker for HIV/TB diagnosis presents a promising research direction:

• Evidence supporting biomarker potential:

  • TB patients show dramatically elevated ZNF134 expression (average 40-fold increase compared to healthy controls)

  • HIV-TB co-infected patients consistently display higher ZNF134 levels than HIV mono-infected individuals

  • Mycobacterial infection induces stronger ZNF134 upregulation than HIV infection alone

• Antibody-based detection optimization strategies:

  • Sample type selection: Evaluate PBMCs, plasma, and dried blood spots for optimal detection sensitivity

  • Assay format development:

    • ELISA with capture/detection antibody pairs targeting different ZNF134 epitopes

    • Flow cytometry for cell-specific ZNF134 expression patterns

    • Lateral flow immunoassays for point-of-care applications

• Clinical validation parameters:

  • Determine sensitivity/specificity in well-defined patient cohorts

  • Establish reference ranges across healthy, HIV+, TB+, and co-infected populations

  • Correlate ZNF134 levels with disease progression markers

• Multiplexed approaches:

  • Combine ZNF134 detection with established TB biomarkers

  • Integrate with HIV viral load measurements for comprehensive assessment

• Technical considerations:

  • Antibody pairs should target non-competing epitopes with minimal cross-reactivity

  • Preanalytical variables (sample collection, processing time) require standardization

  • Detection thresholds should be established through ROC analysis

Research suggests ZNF134 could serve as a biological marker particularly valuable for TB and HIV-TB co-infection scenarios, potentially addressing diagnostic challenges in resource-limited settings .

What are the key considerations for successfully implementing ChIP assays using ZNF134 antibodies?

Implementing ChIP assays with ZNF134 antibodies requires careful methodological considerations:

• Antibody selection criteria:

  • Choose antibodies specifically validated for ChIP applications

  • Prefer antibodies targeting DNA-binding domains or regions not involved in chromatin interaction

  • Consider using multiple antibodies targeting different epitopes for validation

• Crosslinking optimization:

  • For ZNF134 (a C2H2 zinc finger protein), standard 1% formaldehyde for 10 minutes at room temperature is a starting point

  • Consider dual crosslinking with disuccinimidyl glutarate (DSG) followed by formaldehyde for improved zinc finger protein detection

• Sonication parameters:

  • Optimize sonication conditions to generate 200-500 bp DNA fragments

  • Monitor shearing efficiency via agarose gel electrophoresis

  • Consider cell-type specific adjustments (neural cells may require different conditions than lymphocytes)

• Controls:

  • Positive control: Include primers for known ZNF134 binding regions (HIV-1 LTR sequences)

  • Negative control: Use IgG from the same species as the ZNF134 antibody

  • Input control: 5-10% of chromatin prior to immunoprecipitation

• Washing stringency:

  • Balance between reducing background and maintaining specific interactions

  • Consider including zinc in buffers (1-10 μM) to preserve zinc finger structure

• Detection strategies:

  • qPCR for targeted analysis of suspected binding sites

  • ChIP-seq for genome-wide binding profile determination

• Validation approaches:

  • Confirm enrichment at HIV-1 LTR regions through qPCR

  • Consider knockdown/overexpression studies to correlate with ChIP signal changes

  • Compare results across multiple cell types with varying ZNF134 expression levels

Following these guidelines will help generate reliable data on ZNF134 chromatin interactions, particularly in the context of HIV-1 transcriptional regulation.

What strategies can address non-specific binding when using ZNF134 antibodies in immunoprecipitation experiments?

Addressing non-specific binding in ZNF134 immunoprecipitation experiments requires systematic optimization:

• Pre-clearing strategy:

  • Pre-clear lysates with protein A/G beads for 1-2 hours prior to adding ZNF134 antibody

  • Include 0.1-0.5% BSA in IP buffer to block non-specific interactions

  • Consider pre-absorption with unrelated IgG to reduce background

• Buffer optimization:

  • Adjust NaCl concentration (150-500 mM) to balance specific binding vs. background

  • Include mild detergents (0.1-0.5% NP-40 or Triton X-100) to reduce non-specific interactions

  • Add zinc (1-10 μM ZnCl₂) to stabilize zinc finger domains

  • Test different buffers for extraction and washing phases separately

• Antibody considerations:

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

  • Compare different ZNF134 antibodies targeting distinct epitopes

  • Consider using magnetic beads instead of agarose for cleaner pull-downs

• Washing optimization:

  • Implement sequential washes with increasing stringency

  • Maintain zinc concentration in wash buffers

  • Include brief centrifugation steps between washes to remove residual buffer

• Validation approaches:

  • Perform reverse IP with interacting partners

  • Include ZNF134 knockdown samples as negative controls

  • Confirm specificity through mass spectrometry of immunoprecipitated complexes

• Alternative approaches:

  • Consider tandem affinity purification with tagged ZNF134 for reduced background

  • Use crosslinking IP (formaldehyde or DSP) for transient interactions

  • Implement proximity-dependent biotinylation (BioID) for interaction studies

The successful application of these strategies should be validated using known ZNF134 interactions, such as its binding to HIV-1 LTR sequences .

How can researchers quantitatively assess ZNF134 levels in patient samples for clinical research studies?

Quantitative assessment of ZNF134 in patient samples requires robust methodological approaches:

• Sample processing protocol:

  • For PBMCs: Isolate via density gradient centrifugation within 4 hours of collection

  • For tissue biopsies: Implement immediate stabilization in RNAlater or flash-freezing

  • Consider paired samples for protein and RNA analyses when possible

• RNA-based quantification:

  • RT-qPCR methodology:

    • Standardize with validated reference genes (β-actin, GAPDH)

    • Implement absolute quantification using standard curves

    • Design primers spanning exon-exon junctions to avoid genomic DNA amplification

  • Digital PCR for absolute quantification without standard curves

  • RNA-seq for contextualizing ZNF134 expression within broader transcriptome changes

• Protein-based quantification:

  • Western blot: Implement densitometry with recombinant protein standards

  • ELISA development: Sandwich ELISA with capture/detection antibody pairs

  • Immunohistochemistry scoring system:

    • 0: No staining

    • 1+: Weak staining (<10% of cells)

    • 2+: Moderate staining (10-50% of cells)

    • 3+: Strong staining (>50% of cells)

• Normalization strategies:

  • For RNA: Geometric mean of multiple reference genes

  • For protein: Total protein normalization or housekeeping proteins

  • Patient-matched control samples when possible

• Reference ranges and thresholds:

  • Establish in healthy controls (n≥20)

  • Determine in HIV+ patients (treatment-naïve and on ART)

  • Define in TB patients (active disease vs. latent infection)

  • Set in HIV-TB co-infected patients

• Data analysis considerations:

  • Non-parametric statistics for patient comparisons (Mann-Whitney, Kruskal-Wallis)

  • Correlation analyses with clinical parameters (CD4 counts, viral load, TB bacterial burden)

  • Longitudinal measurements to assess treatment responses

Historical data indicates TB patients show approximately 40-fold higher ZNF134 transcript levels compared to healthy controls, providing a baseline for expected effect sizes in clinical studies .

What approaches could researchers use to investigate the regulatory mechanisms controlling ZNF134 expression during mycobacterial infection?

Investigating regulatory mechanisms of ZNF134 during mycobacterial infection requires multifaceted experimental approaches:

• Promoter analysis:

  • Clone the ZNF134 promoter region into reporter constructs

  • Perform deletion/mutation analysis to identify mycobacteria-responsive elements

  • Conduct luciferase assays in cells with/without mycobacterial components

• Transcription factor identification:

  • Employ promoter pull-down assays followed by mass spectrometry

  • Perform ChIP-seq for candidate transcription factors (NF-κB, STAT1, IRFs)

  • Validate with siRNA knockdown of identified factors

• Signaling pathway investigation:

  • Systematically inhibit key pathogen-recognition pathways:

    • TLR2/TLR4 pathways (using blocking antibodies or inhibitors)

    • NOD1/NOD2 signaling

    • cGAS-STING pathway

    • Inflammasome activation

  • Monitor ZNF134 expression changes via qRT-PCR and Western blot

• Epigenetic regulation assessment:

  • Profile DNA methylation changes at the ZNF134 locus during infection

  • Characterize histone modifications via ChIP-seq (H3K4me3, H3K27ac)

  • Test effects of HDAC inhibitors on infection-induced ZNF134 expression

• Post-transcriptional regulation:

  • Identify and validate miRNAs targeting ZNF134 mRNA

  • Assess mRNA stability changes during infection

  • Examine polysome profiling to evaluate translational efficiency

• Mycobacterial component identification:

  • Test purified mycobacterial PAMPs (LAM, 19kDa lipoprotein, etc.)

  • Compare effects of live vs. heat-killed bacteria

  • Evaluate secreted factors via filtered culture supernatants

• Systems biology approach:

  • Integrate transcriptomics, proteomics, and network analysis

  • Identify hub regulators controlling ZNF134 and related genes

  • Validate predictions with targeted experiments

These approaches would help elucidate why TB patients exhibit approximately 40-fold higher ZNF134 transcript levels compared to healthy controls .

How might researchers develop novel therapeutic approaches targeting ZNF134 for HIV-TB co-infection management?

Developing therapeutic approaches targeting ZNF134 for HIV-TB co-infection involves several strategic research directions:

• Small molecule inhibitor development:

  • Structure-based drug design: Utilize structural information about ZNF134's DNA-binding domains

  • High-throughput screening: Test compound libraries against ZNF134-LTR interactions

  • Focused library approach: Target compounds known to interact with C2H2 zinc finger motifs

  • Validation cascade:

    • Biochemical assays (FRET, AlphaScreen) to confirm target engagement

    • Cell-based reporter assays using HIV-1 LTR-driven expression systems

    • Ex vivo testing in patient-derived cells

• RNA interference therapeutic approaches:

  • siRNA delivery systems: Develop nanoparticle or lipid-based formulations

  • shRNA expression cassettes: For stable, long-term knockdown

  • CRISPR/Cas13 systems: For RNA-targeting applications

  • Cell-type specific delivery: Target primary reservoirs of HIV-TB co-infection

• Peptide-based inhibitors:

  • Design competitive inhibitors mimicking ZNF134 DNA-binding domains

  • Develop cell-penetrating peptides targeting ZNF134 protein-protein interactions

  • Create stapled peptides for enhanced stability and cellular uptake

• Immunomodulatory approaches:

  • Evaluate whether normalizing ZNF134 levels impacts immune responses to both pathogens

  • Develop strategies to counteract ZNF134-mediated effects without direct inhibition

• Synergy evaluation:

  • Test ZNF134-targeting approaches in combination with:

    • Conventional antiretrovirals

    • Anti-TB medications

    • Host-directed therapies

• Preclinical model development:

  • Establish humanized mouse models recapitulating ZNF134 regulation

  • Validate ex vivo systems using cells from co-infected patients

  • Develop organoid models incorporating immune components

• Safety assessment considerations:

  • Evaluate off-target effects on other zinc finger proteins

  • Assess impact on essential cellular functions

  • Monitor for unexpected immune consequences

Research showing that 36±5% knockdown of ZNF134 results in 43±10.3% decrease in viral transcripts suggests therapeutic potential, though careful investigation of cellular dependence on ZNF134 is warranted given observations about cell viability during knockdown experiments .

What methodological approaches can address the challenges of studying ZNF134 function in primary patient samples?

Studying ZNF134 function in primary patient samples presents unique challenges requiring specialized methodological approaches:

• Sample preservation and processing:

  • Cryopreservation protocol: Optimize DMSO concentration and freezing rate for different cell types

  • Direct ex vivo analysis: Process samples within 2-4 hours of collection

  • RNA stabilization: Use specialized collection tubes containing RNAlater or similar reagents

  • Single-cell approaches: Implement immediate fixation for scRNA-seq applications

• Limited material optimization:

  • Microscaled assays: Adapt Western blot, ChIP, and IP protocols for microvolumes

  • Sample splitting strategies: Allocate portions for parallel protein/RNA analyses

  • Signal amplification techniques: Consider proximity ligation assays or rolling circle amplification

  • Nested PCR approaches: For transcript detection in limiting samples

• Functional studies in patient-derived cells:

  • Ex vivo infection models: Establish standardized protocols for HIV and/or mycobacterial infection

  • Nucleofection optimization: Determine cell-type specific parameters for primary cells

  • CRISPR ribonucleoprotein delivery: For transient gene editing without vector integration

  • Viral vector transduction: Compare lentiviral vs AAV for different primary cell types

• Cell subset analysis:

  • Flow cytometry panels: Design for simultaneous assessment of ZNF134 with lineage markers

  • Cell sorting strategies: Optimize for viability and downstream applications

  • Imaging flow cytometry: For subcellular localization in rare cell populations

  • Mass cytometry: For comprehensive phenotyping with ZNF134 detection

• Heterogeneity management:

  • Patient stratification: Consider HIV treatment status, TB disease type, and co-morbidities

  • Longitudinal sampling: Track individual patients over treatment course

  • Single-cell technologies: Resolve cell-to-cell variation in ZNF134 expression

  • Reference standards: Include universal controls across experiments

• Comparative experimental design:

  • Matched comparisons: HIV+ vs. HIV-TB co-infected from same geographic regions

  • Control selection: Age/sex matched healthy donors from similar populations

  • Technical replicates: Emphasized for limited and variable primary samples

These approaches address the challenges observed in previous ZNF134 research, where patient samples showed variable but consistently elevated ZNF134 expression during TB and HIV-TB co-infection .