HNRNPLL Antibody

What is HNRNPLL and what is its primary function in cellular processes?

HNRNPLL (heterogeneous nuclear ribonucleoprotein L-like) is an RNA-binding protein that functions as a critical regulator of alternative splicing for multiple target mRNAs. The canonical protein in humans has 542 amino acid residues with a molecular weight of approximately 60.1 kDa . HNRNPLL preferentially recognizes CA dinucleotide-containing sequences in introns and 3′ untranslated regions (UTRs) . It promotes exon inclusion or exclusion in a context-dependent manner and stabilizes mRNA when associated with 3′ UTRs . This protein plays a vital role in rewiring transcriptomes during cell differentiation, particularly in terminally differentiated lymphocytes, including effector T cells and plasma cells .

How is HNRNPLL expression regulated across different cell types and developmental stages?

HNRNPLL expression varies significantly across different cell lineages and developmental stages. In B cell development, HNRNPLL is expressed at low levels in naive and activated B cells but is substantially upregulated (approximately 20-fold increase) in terminally differentiated plasma cells . Similarly, in T cell lineages, HNRNPLL expression is detected in naive CD4 T cells with transcript levels doubling upon 72-hour activation with anti-CD3/CD28 . CD4+CD44+ memory T cells show greater HNRNPLL expression than CD4+CD44− naive T cells . Interestingly, while HNRNPLL is highly expressed in plasma cells, its paralog HNRNPL is more consistently expressed across B cell subpopulations (follicular, marginal zone, and germinal center B cells) . This differential expression pattern suggests tissue-specific regulatory mechanisms controlling HNRNPLL expression.

What techniques are most effective for studying HNRNPLL binding sites on RNA transcripts?

For identifying genome-wide HNRNPLL binding sites, Photoactivatable-Ribonucleoside-Enhanced Cross-Linking and Immunoprecipitation (PAR-CLIP) has proven highly effective. The methodology involves:

• Pulsing cells with photoreactive ribonucleoside analogs (e.g., 4-thiouracil) for 12-14 hours

• UV irradiation (365 nm) to induce covalent RNA-protein cross-linking

• Immunoprecipitation of HNRNPLL and bound RNAs using specific antibodies

• SDS-PAGE separation and visualization with RNA dye (SYBR green II)

• RNA extraction, library preparation, and next-generation sequencing

A key advantage of PAR-CLIP is that polymerases used to reverse-transcribe the cross-linked RNAs introduce specific T-to-C mutations within or near the protein-binding sites, validating the binding specificity and mapping sites at near single-nucleotide resolution . This approach has successfully identified ~110,000 HNRNPLL-binding sites across ~6,000 genes in plasma cells .

For targeted analysis of HNRNPLL-RNA interactions, RNA immunoprecipitation (RIP) followed by qRT-PCR provides a reliable methodology to quantify specific transcripts bound to HNRNPLL .

What are the optimal conditions for Western blotting when detecting HNRNPLL?

For optimal Western blotting detection of HNRNPLL, researchers should consider the following parameters:

For optimal results, it's important to validate the specificity of anti-HNRNPLL antibodies by including appropriate controls, such as cell lines with HNRNPLL knockdown . When working with plasma cells, researchers should be aware that both the canonical HNRNPLL isoform and a higher molecular weight isoform (generated through the use of a noncanonical translational start site located 5' of the canonical ATG) may be detected .

How can I effectively design knockdown experiments to study HNRNPLL function?

Effective HNRNPLL knockdown experiments can be designed using the following approach:

• Selection of appropriate cell model: Plasmacytoma cell lines (e.g., MPC11) have been successfully used for HNRNPLL functional studies .

• Knockdown vector selection: Lentiviral vectors expressing short hairpin RNAs (shRNAs) targeting HNRNPLL have shown high efficiency. Specifically:

  • pLKO.1 lentiviral vectors encoding HNRNPLL-targeted shRNAs

  • Validated shRNA sequences: TRCN0000123505 (LV-hnRNPLL-2)

• Transduction and selection protocol:

  • Transduce cells with lentivirus

  • Select transduced cells with puromycin

  • Achieve ~80% knockdown of HNRNPLL mRNA transcripts

• Validation of knockdown:

  • qRT-PCR to measure HNRNPLL transcript levels

  • Western blotting to confirm protein depletion

  • Flow cytometry with intracellular staining can also verify knockdown

• Functional readouts:

  • Alternative splicing analysis via qRT-PCR assays using exon-specific primers

  • RNA-seq for genome-wide splicing analysis using programs like MISO (Mixture of Isoforms)

  • Analysis of target gene expression using qRT-PCR or RNA-seq

For in vivo studies, conditional knockout models using systems like CD21-cre have been effective in studying HNRNPLL function specifically in peripheral B cells .

How does HNRNPLL contribute to plasma cell differentiation and antibody production?

HNRNPLL plays a critical role in plasma cell differentiation and antibody production through several mechanisms:

• Regulation of IgH pre-mRNA processing: HNRNPLL directly associates with IgH pre-mRNA transcripts and facilitates the exclusion of the secretory poly(A) (secp(A)) exon. This process helps regulate the ratio of membrane-bound to secreted immunoglobulin. In plasmacytoma cells, depletion of HNRNPLL leads to a twofold reduction in the ratio of membrane to secreted IgH mRNA .

• Genome-wide alternative splicing program: During B-cell to plasma-cell differentiation, HNRNPLL mediates a genome-wide switch of RNA processing. This includes alternative splicing events that are crucial for plasma cell function .

• Downregulation of B-cell-specific transcription factors: HNRNPLL directly contributes to the loss of B-cell lymphoma 6 (Bcl6) expression, which is a hallmark of plasma-cell maturation .

• Maximizing immunoglobulin production: Through its RNA binding and processing activities, HNRNPLL helps maximize immunoglobulin production in plasma cells .

• Post-transcriptional regulation of mRNA stability: In addition to splicing regulation, HNRNPLL stabilizes mRNAs when associated with 3′ UTRs, which may contribute to the appropriate expression of plasma cell-specific genes .

Experimental evidence from mixed bone marrow chimera experiments shows that mice reconstituted with HNRNPLL-deficient B cells demonstrate an approximately 8-fold defect in antibody response following immunization with NP-OVA, indicating a cell-intrinsic defect in activated B cells .

What specific RNA targets of HNRNPLL are critical for B cell function?

Several key RNA targets of HNRNPLL have been identified as critical for B cell function:

• Immunoglobulin heavy chain (Ighg2b): HNRNPLL directly binds to Ighg2b transcripts, with major binding peaks identified within the H and CH2 exons. This binding regulates the ratio of membrane-bound versus secreted immunoglobulin transcripts, which is crucial for plasma cell function .

• CD44: CD44 is a known target of HNRNPLL in lymphocytes. RNA immunoprecipitation studies have shown strong enrichment of CD44 mRNA transcripts in HNRNPLL immunoprecipitates from plasmacytoma cells .

• Bcl6: HNRNPLL mediates the down-regulation of Bcl6, a transcription factor that needs to be repressed for complete plasma cell differentiation .

• RNA processing factors: Gene Ontology analysis of transcripts bound by HNRNPLL revealed enrichment for genes related to RNA processing, suggesting that HNRNPLL regulates networks of other RNA-binding proteins and splicing factors .

• Epigenetic regulators: Recent research suggests HNRNPLL may be implicated in the alternative splicing of epigenetic regulators, contributing to the epigenetic landscape changes during B cell activation .

PAR-CLIP experiments have identified approximately 6,000 genes whose transcripts are bound by HNRNPLL in plasma cells, indicating that HNRNPLL has a broad impact on the plasma cell transcriptome .

How can I distinguish between the roles of HNRNPL and HNRNPLL in B cell development?

Distinguishing between HNRNPL and HNRNPLL functions in B cell development requires careful experimental design considering their differential expression patterns and partially overlapping functions:

• Expression pattern analysis:

  • HNRNPL is consistently expressed across B cell subpopulations (follicular, marginal zone, germinal center B cells)

  • HNRNPLL is minimally expressed in quiescent B cells and is upregulated primarily in plasmablasts and plasma cells

  • Quantitative comparison shows HNRNPL expression is substantially higher than HNRNPLL in all B cell stages except terminally differentiated plasma cells

• Cell-specific knockout models:

  • Use CD21-cre system for HNRNPL or HNRNPLL deletion specifically in peripheral B cells

  • Compare phenotypes of single knockouts to identify unique functions

  • Mixed bone marrow chimera experiments can help identify cell-intrinsic effects

• Target identification:

  • Perform comparative PAR-CLIP or RNA immunoprecipitation experiments for both proteins

  • Analyze binding motif preferences (HNRNPLL prefers CA dinucleotide-containing sequences)

  • Compare genome-wide splicing patterns using RNA-seq in cells with HNRNPL or HNRNPLL depletion

• Functional complementation assays:

  • Express HNRNPL in HNRNPLL-deficient cells to determine if HNRNPL can rescue specific phenotypes

  • Create chimeric proteins exchanging domains between HNRNPL and HNRNPLL to identify which domains confer specific functions

• Stage-specific analysis:

  • Examine effects of depletion at different B cell developmental stages (naive, activated, germinal center, plasma cells)

  • HNRNPLL appears more critical in plasma cells, while HNRNPL functions throughout B cell development

Research has shown that while HNRNPLL expression is largely restricted to plasma cells in the B cell lineage, HNRNPL is more broadly expressed, suggesting distinct temporal roles during B cell development and differentiation .

How does HNRNPLL regulate CD45 alternative splicing in T cells?

HNRNPLL regulates CD45 (encoded by the PTPRC gene) alternative splicing in T cells through specific mechanisms:

• Binding to activation response sequences (ARS):

  • The amino-terminal RRM domain of HNRNPLL binds with sequence specificity to ARS motifs present in CD45 exons 4, 5, and 6

  • This binding occurs with micromolar affinity and mediates exon silencing in activated T cells

• Exon-specific regulation:

  • HNRNPLL primarily promotes exclusion of CD45 exons 4 and 6

  • In wild-type T cells with normal HNRNPLL function, exons 4 and 6 show significantly lower inclusion rates compared to other CD45 exons

  • In HNRNPLL-deficient T cells, inclusion of exons 4 and 6 increases substantially

• Developmental regulation:

  • HNRNPLL expression increases during T cell activation and memory T cell development

  • This increased expression correlates with switching from CD45RA to CD45RO isoforms

• Experimental validation:

  • Depletion of HNRNPLL from human T cells by shRNA expression results in increased inclusion of exons 4 to 6

  • Conversely, overexpression of HNRNPLL cDNA in human T cells induces silencing of PTPRC exon 4

RNA-seq analysis of HNRNPLL-deficient T cells (carrying the "thunder" mutation that destabilizes the amino-terminal RRM domain) versus wild-type T cells clearly demonstrates the critical role of HNRNPLL in CD45 isoform switching .

What methodological approaches are most effective for studying HNRNPLL function in T cells?

Several methodological approaches have proven effective for studying HNRNPLL function in T cells:

• Genetic models:

  • The "thunder" mouse model, which carries a loss-of-function point mutation in the HNRNPLL gene that destabilizes the amino-terminal RRM domain

  • Transgenic OT-1 T-cell receptor mice (provides uniform TCR specificity) combined with HNRNPLL mutations for controlled T cell analysis

• RNA analysis techniques:

  • RNA-seq to comprehensively identify splicing changes in HNRNPLL-deficient T cells

  • Targeted RT-PCR with exon-specific primers to validate specific splicing events

  • Analysis of intron retention patterns surrounding regulated exons

• Protein-RNA interaction studies:

  • RNA immunoprecipitation to identify direct RNA targets

  • In vitro binding assays to measure affinity of HNRNPLL RRM domains to target RNA sequences

  • PAR-CLIP to map binding sites at near single-nucleotide resolution

• Functional assays:

  • Flow cytometry to track CD45 isoform expression on cell surface

  • T cell persistence and survival assays to measure functional consequences of HNRNPLL deficiency

  • T cell activation assays to assess impact on signaling events

• Complementation studies:

  • Expression of wild-type or mutant HNRNPLL in deficient cells to identify critical domains

  • Isolation of specific T cell subsets (naive vs. memory) to assess stage-specific functions

These approaches have revealed that HNRNPLL functions extend beyond CD45 regulation to control other genes contributing to T cell persistence and function .

How can conflicts in HNRNPLL antibody specificity and sensitivity be resolved in complex tissue samples?

When facing conflicts in HNRNPLL antibody specificity and sensitivity in complex tissue samples, researchers can implement several strategies:

• Validation with multiple antibodies targeting different epitopes:

  • Use antibodies recognizing distinct regions of HNRNPLL (e.g., middle region vs. N-terminal region)

  • Compare staining patterns and molecular weights in Western blot

  • Commercially available antibodies like 26769-1-AP have been validated for multiple applications

• Inclusion of genetic controls:

  • Include HNRNPLL knockdown or knockout samples as negative controls

  • Verify antibody specificity through decreased staining in knockdown samples

  • Consider using cell lines with CRISPR-Cas9 edited HNRNPLL

• Cross-validation with multiple detection methods:

  • Combine Western blot with immunohistochemistry and immunofluorescence

  • Use RNA-level detection (RNA-FISH or single-cell RNA-seq) to correlate with protein detection

  • Implement proximity ligation assays to confirm specific protein-protein interactions

• Optimized sample preparation and antigen retrieval:

  • For IHC applications, test both TE buffer pH 9.0 and citrate buffer pH 6.0 for antigen retrieval

  • Titrate antibody concentrations (1:50-1:500 range) to determine optimal signal-to-noise ratio

  • Consider tissue-specific fixation protocols that preserve epitope accessibility

• Isoform-specific detection:

  • Be aware that HNRNPLL exists in multiple isoforms (5 reported isoforms from alternative splicing)

  • The canonical isoform and a higher molecular weight isoform (using noncanonical translation start site) may both be present in plasma cells

  • Design experiments to distinguish between these isoforms when necessary

When publishing results, always report the specific antibody clone, dilution, incubation conditions, and validation methods used to ensure reproducibility .

What are the most effective strategies for integrating HNRNPLL binding data with transcriptome-wide splicing analysis?

Integrating HNRNPLL binding data with transcriptome-wide splicing analysis requires sophisticated computational and experimental approaches:

• Comprehensive data collection:

  • Perform PAR-CLIP to identify HNRNPLL binding sites genome-wide

  • Conduct RNA-seq on matched samples with and without HNRNPLL depletion

  • Include appropriate biological replicates (minimum of 2-3) for statistical robustness

• Computational integration pipeline:

  • Use specialized software like MISO (Mixture of Isoforms) to identify alternative splicing events

  • Calculate ψ (PSI; percentage spliced in) scores to quantify exon inclusion rates

  • Correlate HNRNPLL binding sites with differentially spliced regions

  • Consider positional effects: HNRNPLL binding can promote either exon inclusion or exclusion depending on binding location relative to exons

• Motif analysis and positional effects:

  • Identify enriched sequence motifs within HNRNPLL binding sites (CA dinucleotide-containing sequences)

  • Analyze the position of binding sites relative to differentially spliced exons

  • Categorize binding patterns by functional outcome (exon inclusion vs. exclusion)

• Functional validation:

  • Design minigene constructs containing identified splicing targets

  • Perform site-directed mutagenesis of putative HNRNPLL binding sites

  • Transfect constructs into cells with and without HNRNPLL to validate direct regulation

• Integrative visualization:

  • Develop genome browser tracks that simultaneously display:

    • RNA-seq read coverage

    • HNRNPLL binding sites with T-to-C conversion rates

    • Predicted splicing events and their ψ scores

    • Sequence conservation across species

This integrated approach has successfully identified that HNRNPLL preferentially recognizes CA dinucleotide-containing sequences in introns and 3′ UTRs, promoting exon inclusion or exclusion in a context-dependent manner .

How can researchers reconcile conflicting data regarding HNRNPLL's role in different cell types?

When faced with conflicting data regarding HNRNPLL's role across different cell types, researchers should implement the following strategies:

• Contextual analysis of cell-type specific factors:

  • Examine expression levels of HNRNPLL cofactors and competing RNA-binding proteins

  • Assess expression of HNRNPLL paralogs (e.g., HNRNPL) that may compensate in certain contexts

  • Consider the broader transcriptional program active in each cell type

• Comparative binding studies:

  • Perform PAR-CLIP or similar techniques across multiple cell types

  • Compare binding patterns and motif preferences

  • Identify cell-type specific binding partners using co-immunoprecipitation followed by mass spectrometry

• Analysis of splice variants and protein isoforms:

  • Characterize HNRNPLL isoform expression across cell types (canonical vs. alternative isoforms)

  • Consider post-translational modifications that may differ between cell types

  • HNRNPLL itself undergoes alternative splicing, yielding at least 5 different isoforms

• Integration of multi-omic data:

  • Combine transcriptome (RNA-seq), binding site (PAR-CLIP), and epigenome data

  • Consider the epigenetic landscape as a factor in HNRNPLL activity

  • Recent evidence suggests HNRNPLL may indirectly influence MYC/E2F programs through context-dependent mechanisms involving the epigenetic landscape

• Evolutionary conservation analysis:

  • Compare HNRNPLL function across species to identify core conserved mechanisms

  • Distinguish between fundamental and cell-type specific roles

  • Recent work has identified a conserved role of HNRNPLL in regulating alternative splicing of epigenetic regulators

Research has shown that while HNRNPLL affects MYC/E2F transcriptional programs across different cell types, the specific mechanisms and target genes differ significantly between contexts. For instance, these programs are downregulated in most cell types but upregulated in HEK293 cells upon HNRNPLL manipulation .