HNRPH1 Antibody Pair

What is HNRPH1 and what are its primary biological functions?

HNRPH1 (Heterogeneous nuclear ribonucleoprotein H1) is a component of the heterogeneous nuclear ribonucleoprotein (hnRNP) complexes that process pre-mRNAs before they become functional, translatable mRNAs in the cytoplasm. This protein plays critical roles in:

• Regulating alternative pre-mRNA splicing in both mammalian and viral systems

• Binding to guanine-rich sequences in RNA, particularly those that can fold into G-quadruplex structures

• Recruiting other splicing factors such as PTBP2 and SRSF3 to modulate alternative splicing in germ cells

• Contributing to meiosis and cell-cell communication processes, particularly in reproductive systems

HNRPH1 functions through its RNA-binding domains to influence splice site selection and exon inclusion/exclusion, thereby affecting protein diversity from limited gene numbers .

How do HNRPH1 antibody pairs differ from single antibodies for research applications?

HNRPH1 antibody pairs typically consist of a capture antibody and a detection antibody (often biotin-conjugated) specifically designed to work together in sandwich ELISA and other immunoassay applications . Key differences include:

• Enhanced specificity through dual epitope recognition, reducing cross-reactivity issues

• Improved sensitivity compared to single antibody approaches

• Versatility for quantitative analyses in complex biological samples

• Standardized protocols designed for complementary antibody function

For example, the CSB-EAP04264 antibody pair uses rabbit-derived antibodies for both capture (CSB-EAP04264C) and detection (CSB-EAP04264D-Biotin) with recommended concentrations of 0.3 μg/ml and 0.5 μg/ml respectively .

What are the optimal buffer conditions for HNRPH1 antibody pairs in ELISA applications?

Optimizing buffer conditions is crucial for successful HNRPH1 detection by antibody pairs. Based on manufacturer recommendations and research protocols:

Recommended buffer composition:

• Capture antibody dilution buffer: PBS pH 7.4 (often with 50% glycerol for storage)

• Blocking buffer: 1-5% BSA in PBS or TBS with 0.05% Tween-20

• Sample dilution buffer: PBS or TBS with 0.05% Tween-20 and 0.5-1% BSA

• Detection antibody dilution buffer: Similar to sample buffer, maintaining pH 7.3-7.4

• Wash buffer: PBS or TBS with 0.05-0.1% Tween-20

For optimal performance when working with HNRPH1:

• Maintain buffer pH between 7.3-7.4, as this matches the storage buffer conditions (0.01M PBS, pH 7.4)

• Include 0.05% NP-40 (IGEPAL CA-630) in immunoprecipitation buffers to improve interaction while minimizing background

• Add protease and RNase inhibitors to buffers when analyzing RNA-protein interactions

Temperature considerations are also important, with binding reactions typically performed at 4°C to preserve protein-antibody interactions .

How should researchers optimize HNRPH1 antibody pair concentrations for different sample types?

Optimizing antibody concentrations is essential for achieving high signal-to-noise ratios across different sample types:

General optimization strategy:

• Initial concentration screening:

  • Start with manufacturer-recommended concentrations (e.g., 0.3 μg/ml for capture and 0.5 μg/ml for detection antibodies)

  • Perform checkerboard titrations with 2-fold serial dilutions of both antibodies

  • Evaluate signal-to-noise ratio rather than absolute signal strength

• Sample-specific adjustments:

  • Cell lysates: Higher antibody concentrations may be needed (1:500-1:2000 dilution range)

  • Tissue extracts: Titrate antibodies with positive control tissues (brain tissue shows high expression)

  • Purified protein: Lower concentrations are typically sufficient

• Validation across sample types:

Remember that experimental conditions should be determined empirically for each specific application and sample type .

What controls should be included when using HNRPH1 antibody pairs for quantitative analysis?

Rigorous controls are essential for reliable quantitative analysis with HNRPH1 antibody pairs:

Essential controls:

• Analytical controls:

  • Standard curve using recombinant HNRPH1 protein (minimum 7-point curve with 2-fold dilutions)

  • Blank controls (buffer only) to establish background signal

  • Isotype controls using non-specific antibodies of the same isotype (e.g., rabbit IgG)

• Biological validation controls:

  • Positive tissue/cell controls (e.g., brain tissue, HEK-293T cells)

  • RNA interference validation (siRNA knockdown samples)

  • HNRPH1-deficient samples when available (e.g., knockout mouse models)

• Specificity controls:

  • Cross-reactivity assessment with related proteins (hnRNP H2, hnRNP F)

  • Peptide competition assays using immunogenic peptides

  • Western blot validation showing expected 49-50 kDa band

For RNA-protein interaction studies, include appropriate controls:

• Input fraction samples (5-10% of starting material)

• Mock immunoprecipitation with non-specific antibodies

• RNase-treated controls to confirm RNA-dependent interactions

How can HNRPH1 antibody pairs be adapted for studying RNA-protein interactions in alternative splicing research?

HNRPH1 antibody pairs can be effectively adapted for studying RNA-protein interactions through several specialized approaches:

RNA immunoprecipitation (RIP) protocols:

• Cross-link protein-RNA complexes using UV (254 nm) or formaldehyde treatment

• Lyse cells in appropriate buffer containing RNase inhibitors and protease inhibitors

• Pre-clear lysate with protein G Dynabeads

• Immunoprecipitate HNRPH1-RNA complexes using capture antibody (5 μg of anti-HNRNPH1) bound to protein G beads

• Wash extensively with TBS-0.05% NP-40 buffer

• Isolate RNA using TRIzol and perform RT-qPCR or RNA-seq analysis

For thermal sensitivity studies of RNA-protein interactions:

• Perform parallel RIP experiments at different temperatures (e.g., 37°C vs 32°C) to study thermosensitive interactions between HNRPH1 and target RNAs like RBM3

• Normalize HNRPH1-pulled down RNA to total RNA levels and immunoprecipitation efficiency

For studying G-rich motif interactions:

• Use biotinylated RNA oligomers containing wild-type or mutated G-rich sequences

• Perform pull-down assays with varying concentrations (40-160 nM) of RNA oligomers

• Analyze by Western blot using anti-HNRNPH1 antibodies to quantify binding

• Include competition assays with non-biotinylated oligos to confirm specificity (IC50 ≈ 84 nM)

What methodological approaches can resolve contradictory data when analyzing HNRPH1 function in different cell types?

Resolving contradictory data regarding HNRPH1 function across different cell types requires systematic methodological approaches:

Tissue-specific expression profiling:

• Perform quantitative western blotting across multiple tissues and cell lines using optimized antibody dilutions (1:1000-1:6000)

• Validate protein expression patterns with immunohistochemistry (IHC) and immunofluorescence (IF) at 1:50-1:500 dilutions

• Correlate protein levels with mRNA expression using RT-qPCR or RNA-seq data

Cell type-specific function analysis:

• Generate conditional knockout models (e.g., Hnrnph1 bKO mice) to assess tissue-specific functions

• Compare phenotypes between germline-specific mutants in both males and females to identify sex-specific differences

• Analyze splicing patterns of known targets across different cell types using RT-PCR and RNA-seq

Resolution strategies for contradictory findings:

• Context-dependent protein interactions:

  • Perform co-immunoprecipitation studies to identify cell type-specific protein partners

  • Compare HNRPH1 interactomes between reproductive tissues (where it recruits PTBP2 and SRSF3) and immune cells (where it regulates class-switched antibody production)

• Substrate competition analysis:

  • Examine G-rich motif distribution across differentially regulated transcripts

  • Compare binding affinity to different G-rich sequences (rG1 > rG2b > rG2a)

  • Test competition between different RNA substrates with varying concentrations

• Post-translational modification characterization:

  • Analyze phosphorylation, methylation, or other modifications that might differ between tissues

  • Correlate modifications with functional differences using modified protein-specific antibodies

How can HNRPH1 antibody pairs be utilized to investigate its role in germinal center responses and antibody class switching?

HNRPH1 antibody pairs can be instrumental in investigating its role in germinal center (GC) responses and antibody class switching through several specialized approaches:

GC B cell isolation and analysis:

• Isolate splenic B cells from wild-type and Hnrnph1 bKO mice following TD antigen challenge

• Sort GC B cells (GL7⁺CD95⁺) using flow cytometry

• Analyze HNRPH1 expression using antibody pairs in ELISA or Western blot applications

• Correlate HNRPH1 levels with GC formation and class-switched antibody production

Analysis of class switching mechanisms:

• Culture B cells with LPS (for IgG3), LPS+IL4 (for IgG1), or anti-CD40+IL4+IL21

• Quantify class switching efficiency by flow cytometry

• Correlate HNRPH1 expression levels with IgG1 vs. IgG3 production

• Analyze splicing patterns of IgG-related transcripts

Key experimental protocol for TD antibody response:

• Challenge mice with NP-CGG antigen

• Collect serum at multiple timepoints (days 7, 14, 21 post-immunization)

• Perform ELISA to measure NP-specific antibody titers of different isotypes

• Assess antibody affinity maturation by comparing binding to NP₂-BSA vs. NP₂₀-BSA

• Measure IgG1⁺ antibody-secreting cells by ELISPOT in spleen and bone marrow

Research has shown that Hnrnph1 bKO mice exhibit:

• Normal NP-specific IgM antibody production

• Significantly decreased class-switched NP-specific IgG1, IgG2b, and IgG3 titers

• Reduced NP-specific IgG1 antibody-secreting cells in spleen and bone marrow

• Compromised antibody affinity maturation (lower NP₂/NP₂₀ binding ratios)

What methodologies can detect the interaction between HNRPH1 and G-quadruplex structures in RNA?

Studying interactions between HNRPH1 and G-quadruplex (G4) structures in RNA requires specialized methodologies:

In vitro binding assays:

• Electrophoretic Mobility Shift Assay (EMSA):

  • Synthesize RNA oligomers containing wild-type G-rich sequences and mutated controls

  • Incubate with purified HNRNH1 protein at varying concentrations

  • Analyze mobility shifts using chemiluminescent detection

  • Include G-to-A mutations to disrupt G4 formation as controls

• Antibody-based RNA binding assays:

  • Use biotinylated RNA oligomers (wild-type and mutated)

  • Incubate with purified HNRPH1

  • Capture RNA-protein complexes with streptavidin beads

  • Detect bound HNRPH1 using specific antibodies

  • Quantify binding enrichment compared to controls

• Competition assays:

  • Perform binding with labeled G4 RNA in the presence of varying concentrations of unlabeled competitor

  • Determine IC50 values for different G4 structures

  • Example: rG1 competition with IC50 of 84 nM

Cellular validation approaches:

• UV crosslinking and immunoprecipitation:

  • Transfect cells with biotinylated G4-containing RNA oligomers

  • UV crosslink to stabilize RNA-protein interactions

  • Pull down with streptavidin beads

  • Detect HNRPH1 by Western blot analysis

• Functional validation:

  • Transfect cells with G4-containing oligomers at varying concentrations (40-160 nM)

  • Analyze effects on known HNRPH1-regulated splicing events

  • Monitor target protein expression changes (e.g., 50% reduction in EWS-FLI1 mRNA at 80-160 nM of G4 oligomers)

How can researchers address low signal-to-noise ratios when using HNRPH1 antibody pairs?

When encountering low signal-to-noise ratios with HNRPH1 antibody pairs, systematic troubleshooting can identify and resolve specific issues:

Optimizing antibody parameters:

• Antibody concentration adjustment:

  • Re-titrate antibody concentrations beyond manufacturer recommendations

  • Test capture antibody at 0.1-1.0 μg/ml (starting from 0.3 μg/ml)

  • Test detection antibody at 0.2-1.0 μg/ml (starting from 0.5 μg/ml)

• Blocking optimization:

  • Test different blocking agents (BSA, casein, commercial blockers)

  • Extend blocking time to 2 hours at room temperature

  • Increase blocking agent concentration to 2-5%

• Buffer adjustments:

  • Ensure antibody storage in 50% glycerol, 0.01M PBS, pH 7.4

  • Add 0.05% Tween-20 to reduce non-specific binding

  • Consider adding 0.05% NP-40 for immunoprecipitation applications

Sample preparation improvements:

• Protein extraction protocols:

  • Use different lysis buffers optimized for nuclear proteins

  • Add protease inhibitors to prevent degradation

  • Include phosphatase inhibitors if studying phosphorylated forms

• Sample clean-up:

  • Pre-clear lysates with protein G beads before assay

  • Ultracentrifuge samples to remove aggregates

  • Consider immunodepletion of abundant proteins

Experimental design modifications:

• Signal amplification strategies:

  • Use streptavidin-HRP conjugates with enhanced sensitivity

  • Implement tyramide signal amplification for immunohistochemistry

  • Consider chemiluminescent substrates with extended signal duration

• Controls to identify source of noise:

  • Run antibody-only controls (no sample)

  • Test cross-reactivity with related proteins (hnRNP H2, hnRNP F)

  • Perform peptide competition assays to confirm specificity

What are the critical variables for reproducible HNRPH1 detection in different experimental systems?

Achieving reproducible HNRPH1 detection across different experimental systems requires attention to several critical variables:

Sample preparation standardization:

• Extraction protocol consistency:

  • Standardize cell lysis buffer composition across experiments

  • Maintain consistent protein:lysis buffer ratios

  • Process samples within the same timeframe to minimize degradation

• Subcellular fractionation:

  • HNRPH1 is predominantly nuclear, so nuclear extraction protocols are critical

  • Include both cytoplasmic and nuclear fractions to track potential redistribution

  • Verify fractionation quality with compartment-specific markers

Technical parameters:

• Antibody lot consistency:

  • Document lot numbers and maintain consistency when possible

  • Perform bridging studies when changing antibody lots

  • Create internal reference standards for normalization

• Temperature control:

  • Maintain consistent incubation temperatures (4°C for immunoprecipitation)

  • Account for temperature sensitivity of HNRPH1-RNA interactions

  • Pre-equilibrate all reagents to working temperature

• Time-dependent variables:

  • Standardize incubation times for capture and detection antibodies

  • Control sample storage time before analysis

  • Document time between tissue collection and processing

Experimental system considerations:

• Cell type-specific concerns:

  Cell/Tissue Type	Critical Variables	Recommendations
  HEK-293T, HeLa, HepG2	High expression levels	Lower antibody concentrations (1:3000-1:6000)
  Brain tissue	High endogenous expression	Include appropriate positive controls
  Reproductive tissues	Context-dependent expression	Standardize sample collection timing
  Immune cells	Class switching dependence	Control activation status of B cells

• Normalization strategy:

  • Use housekeeping proteins appropriate for nuclear fraction

  • Consider normalizing to total protein load (Ponceau staining)

  • Include recombinant HNRPH1 standards for absolute quantification

How can researchers distinguish between HNRPH1 and other closely related hnRNP family proteins?

Distinguishing HNRPH1 from closely related hnRNP family proteins (particularly HNRPH2/H'/HNRNPH2 and hnRNP F) requires careful methodological approaches:

Antibody selection and validation:

• Epitope mapping:

  • Select antibodies targeting unique regions of HNRPH1

  • Avoid antibodies targeting conserved RNA recognition motifs (RRMs)

  • Validate specificity against recombinant HNRPH1, HNRPH2, and hnRNP F proteins

• Cross-reactivity testing:

  • Perform western blots with recombinant proteins of all three family members

  • Test with lysates from cells overexpressing each protein individually

  • Validate with siRNA knockdown of individual family members

Advanced discrimination techniques:

• Two-dimensional gel electrophoresis:

  • Separate proteins by isoelectric point and molecular weight

  • HNRPH1 and related proteins have slightly different migration patterns

  • Follow with western blotting using specific antibodies

• Mass spectrometry identification:

  • Immunoprecipitate with HNRPH1 antibodies

  • Analyze peptide fragments by mass spectrometry

  • Identify unique peptide signatures that distinguish between family members

• RNA-binding specificity:

  • Compare binding patterns to different G-rich RNA sequences

  • Analyze differential affinity for specific RNA structures

  • Use competition assays to determine binding preferences

Experimental approaches to distinguish functions:

• Selective knockdown:

  • Design siRNAs targeting unique regions of each family member

  • Validate knockdown specificity by qPCR and western blot

  • Compare phenotypic effects on alternative splicing patterns

• Recombinant protein replacement:

  • Knockdown endogenous protein and replace with tagged versions

  • Introduce mutations in family-specific regions

  • Assess functional rescue to determine specific contributions

Key distinguishing features:

• HNRPH1: 49 kDa protein, primarily nuclear localization

• HNRPH2/H': Similar molecular weight but encoded by X-linked gene

• hnRNP F: Slightly lower molecular weight (46 kDa), different RNA binding preferences

How can HNRPH1 antibody pairs be utilized for studying temperature-dependent RNA processing mechanisms?

HNRPH1 antibody pairs can be effectively deployed to study temperature-dependent RNA processing mechanisms, particularly in relation to cold-shock responses:

Temperature-controlled immunoprecipitation protocols:

• Set up parallel experimental conditions at different temperatures (e.g., 37°C vs. 32°C)

• Prepare cell extracts at the respective temperatures

• Perform RNA immunoprecipitation (RIP) using anti-HNRNPH1 antibodies (5 μg per IP)

• Isolate RNA using TRIzol from both input and immunoprecipitated fractions

• Analyze temperature-dependent binding patterns by RT-qPCR or RNA-seq

Key methodological considerations:

• Maintain consistent temperature throughout all experimental steps

• Normalize HNRNPH1-pulled down RNA to total RNA levels and immunoprecipitation efficiency

• Include controls for temperature-dependent changes in antibody binding kinetics

Application to cold-shock protein regulation:
Research has shown that HNRNPH1 mediates cold-dependent exon skipping via thermosensitive interaction with G-rich motifs within poison exons of the neuroprotective cold-shock protein RBM3 . This can be studied by:

• Analyzing temperature-dependent binding of HNRNPH1 to RBM3 transcripts

• Quantifying exon inclusion/skipping rates at different temperatures

• Correlating binding strength with splicing outcomes

• Examining how HNRNPH1 levels affect cold adaptation responses

Experimental workflow for thermal sensitivity studies:

• Culture cells at normal (37°C) and cold-shock (32°C) temperatures

• Harvest cells and perform RNA-IP with HNRNPH1 antibodies

• Analyze bound transcripts by RT-qPCR focusing on temperature-sensitive targets

• Compare binding efficiency at different temperatures normalized to protein levels

• Correlate with alternative splicing outcomes using exon-specific primers

What methodological approaches can assess the role of HNRPH1 in regulating RNA G-quadruplex structures in oncogenic contexts?

Investigating HNRPH1's role in regulating RNA G-quadruplex (G4) structures in oncogenic contexts requires specialized methodological approaches:

Detection of G4-HNRPH1 interactions in cancer models:

• Cell line selection:

  • Use paired normal/cancer cell lines from the same tissue origin

  • Include cancer cell lines with known G4-regulated oncogenes (e.g., EWS-FLI1 in Ewing sarcoma)

• G4-specific pulldown assays:

  • Design biotinylated RNA oligomers containing G4-forming sequences from oncogenes

  • Transfect at varying concentrations (40-160 nM) into cancer cells

  • Pull down with streptavidin beads and detect HNRPH1 by western blot

  • Compare binding efficiency between wild-type G4 sequences and G→A mutated controls

• Functional validation:

  • Monitor oncogene expression levels after G4 oligomer transfection

  • Quantify by qPCR and western blot (e.g., 50% reduction in EWS-FLI1 mRNA)

  • Assess downstream effects on cancer cell phenotypes (proliferation, migration)

G4-targeted therapeutic approaches:

• G4-stabilizing compounds in combination with HNRPH1 modulation:

  • Test G4-stabilizing small molecules (e.g., pyridostatin, BRACO-19)

  • Combine with HNRPH1 knockdown or overexpression

  • Measure synergistic effects on oncogene expression and cancer cell viability

• Custom G4-targeting oligonucleotides:

  • Design oligonucleotides matching specific oncogenic G4 structures

  • Include chemical modifications to enhance stability and cellular uptake

  • Monitor competition with endogenous HNRPH1 binding

  • Assess functional outcomes on oncogene splicing and expression

Experimental validation in patient-derived samples:

• Analyze HNRPH1 expression levels across tumor types using tissue microarrays

• Correlate with expression of G4-regulated oncogenes

• Perform RNA-IP on patient-derived xenograft models

• Compare G4-binding patterns between primary tumors and metastatic lesions

What techniques can be used to investigate the role of HNRPH1 in neurological disorders and neuroprotective mechanisms?

Investigating HNRPH1's role in neurological disorders and neuroprotective mechanisms requires specialized techniques leveraging antibody-based detection:

Tissue-specific expression analysis:

• Brain region-specific profiling:

  • Use immunohistochemistry with HNRPH1 antibodies (1:50-1:500 dilution)

  • Compare expression across different brain regions (cortex, hippocampus, cerebellum)

  • Correlate with regions affected in specific neurological disorders

  • Perform dual labeling with neuronal/glial markers to identify cell type-specific expression

• Expression in disease models:

  • Analyze HNRPH1 levels in animal models of neurodegeneration

  • Compare with post-mortem human brain samples from patients with neurological disorders

  • Perform western blotting with optimized antibody dilutions (1:1000-1:6000)

HNRPH1-mediated neuroprotective mechanisms:

• Cold-shock protein regulation:

  • Study HNRPH1's thermosensitive interaction with RBM3 G-rich motifs

  • Compare binding at normal vs. cold-shock temperatures

  • Analyze alternative splicing patterns of neuroprotective factors

  • Correlate with cellular resistance to stress conditions

• Splicing regulation in neurons:

  • Identify neuron-specific HNRPH1 RNA targets using CLIP-seq

  • Validate with RNA-IP using optimized antibody concentrations

  • Compare splicing patterns between normal and stress conditions

  • Correlate with neuronal survival and function

Experimental approaches for therapeutic development:

• HNRPH1 modulation strategies:

  • Design antisense oligonucleotides targeting HNRPH1-regulated splice sites

  • Test small molecules that modify HNRPH1-RNA interactions

  • Evaluate effects on neuronal survival in stress conditions

• Biomarker development:

  • Measure HNRPH1 levels and activity in accessible biofluids

  • Correlate with disease progression in longitudinal studies

  • Develop ELISA-based detection using optimized antibody pairs

• Functional rescue experiments:

  • Modulate HNRPH1 levels in neuronal cultures using viral vectors

  • Challenge with stressors relevant to specific neurological disorders

  • Assess neuroprotective effects through viability and functional assays

  • Validate key splicing targets that mediate protective effects