RNASEL Antibody

What is RNASEL and what role does it play in cellular immunity?

RNASEL (ribonuclease L, also known as RNS4) is an endoribonuclease that functions as a critical component of the interferon (IFN) antiviral response pathway. In IFN-treated and virus-infected cells, RNASEL mediates antiviral effects through multiple mechanisms: direct cleavage of single-stranded viral RNAs, inhibition of protein synthesis via rRNA degradation, induction of apoptosis, and activation of other antiviral genes . The protein functions as part of the 2′,5′-oligoadenylate (2-5A) synthetase-RNase L system, which is a key innate immune defense mechanism. RNASEL-mediated apoptosis occurs through a JNK-dependent stress-response pathway that leads to cytochrome c release from mitochondria and subsequent caspase-dependent apoptosis . This mechanism helps eliminate virus-infected cells under certain conditions, making RNASEL a crucial factor in host defense against viral pathogens.

What are the recommended applications for RNASEL antibodies in research?

RNASEL antibodies can be utilized in multiple experimental applications depending on research objectives. Western Blot (WB) is the most commonly validated application, with recommended dilutions typically ranging from 1:1000-1:4000 . Immunohistochemistry (IHC) is effective at dilutions between 1:20-1:200, particularly in human tonsillitis and spleen tissues with suggested antigen retrieval using TE buffer (pH 9.0) or alternatively citrate buffer (pH 6.0) . Immunofluorescence/Immunocytochemistry (IF/ICC) works effectively at 1:50-1:500 dilutions and has been validated in several cell lines including HepG2 cells . ELISA applications have also been documented in literature . When designing experiments, it is advisable to titrate the antibody in each testing system to obtain optimal results as sensitivity can be sample-dependent.

How do I optimize antigen retrieval when performing IHC with RNASEL antibodies?

For optimal antigen retrieval when performing immunohistochemistry with RNASEL antibodies, the primary recommendation is to use TE buffer at pH 9.0 . If this approach yields suboptimal results, an alternative method using citrate buffer at pH 6.0 can be implemented . The effectiveness of antigen retrieval can vary depending on tissue fixation methods, embedding techniques, and tissue types. For tissues with high protein content or dense connective tissue components, extending the antigen retrieval time may improve antibody penetration. It is advisable to include positive control tissues such as human tonsillitis or spleen tissue, where RNASEL expression has been consistently detected . When troubleshooting weak staining, consider adjusting both the antigen retrieval method and primary antibody concentration, while maintaining consistent incubation times and temperatures to ensure reproducible results.

How does the OAS-RNASEL pathway function in viral infections, and which components are essential for RNASEL activation?

The OAS-RNASEL pathway represents a critical antiviral mechanism in which double-stranded RNA (dsRNA) produced during viral infections activates OAS proteins to synthesize 2′,5′-oligoadenylates (2-5A), which subsequently bind to and activate RNASEL. Research has definitively demonstrated that among the three enzymatically active OAS proteins in humans (OAS1, OAS2, and OAS3), OAS3 is the primary contributor to RNASEL activation during viral infections . Studies using CRISPR-Cas9 engineered cell lines with specific OAS gene knockouts revealed that OAS3-KO cells synthesized minimal 2-5A and failed to activate RNASEL upon infection with diverse viruses including West Nile virus, Sindbis virus, influenza virus, and vaccinia virus . Mechanistically, OAS3 displays a higher affinity for dsRNA in intact cells compared to OAS1 or OAS2, explaining its dominant role in RNASEL activation . This pathway functions as an essential innate immune response that restricts viral replication, as evidenced by increased viral yields in OAS3-KO or RNASEL-KO cells compared to wild-type cells . Understanding this pathway hierarchy is crucial when designing experiments targeting specific components of antiviral immunity.

What is the relationship between RNASEL and inflammasome activation during viral infections?

RNASEL plays a significant role in inflammasome activation during viral infections, particularly in relation to the NLRP3 inflammasome. Research has shown that RNASEL activation enhances inflammasome responses, which contribute to the production of pro-inflammatory cytokines like IL-1β . The mechanism involves RNASEL-mediated cleavage of viral and cellular RNAs, which generates RNA fragments that serve as potent activators of the NLRP3 inflammasome. Experimental evidence demonstrates that transfection with cleaved RNA (either viral or cellular) leads to enhanced inflammasome activation compared to intact RNAs . In vivo studies with RNASEL-deficient mice showed reduced production of IL-1β and IFN-β during influenza A virus infection, correlating with decreased survival and increased viral titers in the lungs . This connection between RNASEL and inflammasome activation represents a crucial link between viral sensing, RNA degradation, and inflammatory responses. When investigating antiviral immune responses, researchers should consider this dual function of RNASEL in both direct antiviral activity and immunomodulation through inflammasome signaling.

How can I effectively use RNASEL antibodies to study the crosstalk between autophagy and apoptosis?

RNASEL antibodies serve as valuable tools for investigating the complex interplay between autophagy and apoptosis pathways, particularly in the context of viral infections. To effectively study this crosstalk, implement a multi-methodological approach combining immunoblotting, immunofluorescence, and functional assays. When designing experiments, consider that RNASEL has been implicated in promoting caspase-dependent proteolytic cleavage of BECN1 (Beclin-1) during prolonged stress, which terminates autophagy and promotes apoptosis . For immunoblotting experiments, use RNASEL antibodies (1:1000-1:4000 dilution) alongside markers for both autophagy (LC3-I/II, p62, BECN1) and apoptosis (cleaved caspases, PARP cleavage) . For spatial and temporal analysis, employ immunofluorescence (1:50-1:500 dilution) to monitor RNASEL localization relative to autophagosomal and mitochondrial markers during stress responses . To capture the dynamic nature of this crosstalk, incorporate time-course experiments following viral infection or dsRNA stimulation, collecting samples at early time points (2-6 hours) to capture initial autophagy induction and later time points (12-24 hours) to observe the transition to apoptosis. Complement antibody-based approaches with functional assays measuring both autophagy flux and apoptotic cell death to correlate RNASEL expression patterns with cellular outcomes.

What is the significance of RNASEL as a potential biomarker in prostate cancer research?

RNASEL has emerged as a potential biomarker in prostate cancer research, although with modest predictive capabilities. Studies evaluating RNASEL specific expression in prostate tissues revealed significant differences between cancerous and healthy specimens, with an area under the curve (AUC) of 0.64 (95% CI = 0.53–0.74, p = 0.013) in receiver operating characteristic analysis . At the optimal cutoff value determined by Youden's index, RNASEL demonstrated a specificity of 86.9% but limited sensitivity of 40.5% . Interestingly, researchers observed an "on-off switch" negative correlation between RNASEL expression in carcinoma specimens versus healthy tissue, with high activity in healthy tissue corresponding to decreased expression in carcinoma tissue and vice versa (correlation coefficient of -0.5) . This expression pattern suggests RNASEL might serve better as part of a biomarker panel rather than as a standalone indicator. When designing studies to investigate RNASEL in cancer contexts, researchers should consider stratifying samples based on inflammatory status, as lymphocytic infiltration was associated with higher RNASEL expression, particularly in control specimens . The integration of RNASEL expression data with histopathological findings and other molecular markers could enhance its utility in prostate cancer research and potential diagnostic applications.

How can I validate the specificity of RNASEL antibodies in my experimental system?

Validating RNASEL antibody specificity is essential for generating reliable research data. A comprehensive validation strategy employs multiple approaches. First, perform Western blotting using positive control lysates from cells known to express RNASEL, such as THP-1 or RAW 264.7 cells . The antibody should detect bands at the expected molecular weights of 84 kDa and/or 73 kDa . Include negative controls using RNASEL-knockout cell lines created via CRISPR-Cas9 technology, which provide definitive evidence of specificity . For immunohistochemistry applications, parallel staining of known positive tissues (human tonsillitis or spleen) alongside experimental samples serves as an important control . Additionally, employ peptide competition assays where pre-incubation of the antibody with its immunogenic peptide should abolish specific staining. For highly sensitive applications, consider orthogonal validation by correlating protein detection with mRNA expression levels using RT-qPCR. When working with new cell lines or tissues, perform serial dilution tests to determine optimal antibody concentration while monitoring signal-to-noise ratios. Finally, compare results obtained with different RNASEL antibodies recognizing distinct epitopes, as concordant results strongly support specificity. This multi-faceted approach ensures confident interpretation of experimental results involving RNASEL detection.

What methodological considerations are important when studying RNASEL enzyme activity versus expression levels?

When investigating RNASEL in research settings, distinguishing between enzyme activity and expression levels requires distinct methodological approaches. For expression analysis, antibody-based techniques like Western blotting (1:1000-1:4000 dilution) provide information about total protein abundance . ELISA methods offer quantitative expression measurements with detection ranges typically between 15.625 and 1000 pg/mL, and results should be normalized to total tissue protein content (ng/g proteins) . Conversely, assessing RNASEL enzymatic activity requires functional approaches that measure the ribonuclease capacity of the protein. One effective strategy employs a FRET-based assay that quantifies 2-5A, which indirectly measures RNASEL activation . When designing activity experiments, consider that RNASEL exists in both free (active) and inhibitor-bound (latent) forms in cells. To distinguish between these pools, incorporate treatments with sulfhydryl reagents (such as 10mM p-chloromercuribenzoate) to dissociate inhibitor complexes, allowing measurement of total (free + inhibitor-bound), free, and latent enzyme activities . Additionally, when interpreting RNASEL activity data, account for inflammatory conditions as confounding factors by stratifying samples based on inflammation type . Finally, for comprehensive analysis, combine activity and expression measurements on the same samples to calculate specific activity (activity/expression ratio), which provides insight into post-translational regulation and inhibitor dynamics affecting RNASEL function.

How can I design experiments to study the interaction between RNASEL and the OAS system in viral immunity?

Designing robust experiments to investigate RNASEL-OAS interactions requires a multi-faceted approach leveraging genetic manipulation, biochemical assays, and virus infection models. First, establish a panel of cell lines with knockout or knockdown of specific OAS family members (OAS1, OAS2, OAS3) and RNASEL using CRISPR-Cas9 or RNAi technology . This genetic approach allows for systematic evaluation of the contribution of each pathway component. To measure 2-5A synthesis and RNASEL activation, implement a FRET-based assay that quantifies 2-5A levels following viral infection or dsRNA stimulation . Complement this with an rRNA degradation assay (bioanalyzer or northern blot analysis) as a direct measure of RNASEL nuclease activity . For viral infection experiments, select diverse virus types (e.g., West Nile virus, Sindbis virus, influenza virus, and vaccinia virus) to evaluate the breadth of the response . Incorporate time-course analyses (2, 4, 8, 12, 24 hours post-infection) to capture the kinetics of OAS expression, 2-5A synthesis, and RNASEL activation. To assess the affinity of different OAS proteins for viral dsRNA, perform RNA immunoprecipitation followed by quantitative PCR or sequencing. Additionally, employ proximity ligation assays or co-immunoprecipitation with RNASEL antibodies to visualize and quantify protein-protein interactions between RNASEL and OAS family members. Finally, validate your in vitro findings using ex vivo primary cells or in vivo models with corresponding genetic alterations in the OAS-RNASEL pathway.

What approaches can I use to investigate the role of RNASEL in regulating mRNA turnover beyond antiviral responses?

To investigate RNASEL's role in mRNA turnover beyond viral contexts, implement a comprehensive experimental strategy combining transcriptome-wide analyses with mechanistic studies. Begin with RNASEL knockout and/or inducible expression systems in relevant cell types using CRISPR-Cas9 technology or doxycycline-regulated expression constructs . For global mRNA stability assessment, perform actinomycin D chase experiments coupled with RNA-seq to compare mRNA half-lives between wild-type and RNASEL-modified cells under basal conditions. To identify direct RNASEL targets, implement CLIP-seq (cross-linking immunoprecipitation followed by sequencing) using RNASEL antibodies, which will map RNASEL binding sites transcriptome-wide . For detailed mechanistic insights, perform in vitro cleavage assays using recombinant RNASEL and candidate mRNA substrates to characterize cleavage patterns, focusing particularly on UU and UA sequences which are preferred RNASEL targets . Complement these approaches with polysome profiling to evaluate how RNASEL activity impacts translation efficiency of specific mRNAs. To investigate regulatory mechanisms, examine RNASEL activity in response to various cellular stresses beyond viral infection (ER stress, oxidative stress, nutrient deprivation) using the rRNA degradation assay as a readout . Additionally, investigate potential cross-talk with other RNA decay pathways by performing co-immunoprecipitation experiments to identify protein-protein interactions between RNASEL and components of P-bodies, stress granules, or the exosome complex. Finally, evaluate the physiological significance of RNASEL-mediated mRNA turnover in processes such as cellular differentiation, stress responses, or cell cycle progression using appropriate cell models.

What controls and normalization methods should I implement when quantifying RNASEL expression across different tissue types?

When quantifying RNASEL expression across diverse tissue types, implementing rigorous controls and normalization methods is essential for generating accurate, comparable data. For immunohistochemical analysis, include both positive control tissues (human tonsillitis and spleen tissue) and negative controls (RNASEL-knockout tissues or primary antibody omission) . To account for tissue-specific baseline expression, establish reference ranges by analyzing multiple samples from healthy individuals representing each tissue type. For quantitative protein expression analysis via Western blot or ELISA, normalize RNASEL signals to total protein content rather than single housekeeping proteins, as the latter may vary significantly across tissues . Consider implementing the RRID (Research Resource Identifier) system (e.g., AB_2631036) to ensure antibody consistency across experiments . For transcript analysis, validate multiple reference genes specific to your tissue panel using algorithms like geNorm or NormFinder, as commonly used housekeeping genes often show tissue-specific variation. When comparing tissues with different cellular compositions, consider cell-type deconvolution approaches or single-cell analyses to account for heterogeneity. For tissues with varying inflammatory status, stratify samples based on inflammatory profiles (lymphocytic, macrophage/neutrophil infiltration, or absence of inflammation) as these significantly impact RNASEL expression . Additionally, implement standard curves using recombinant RNASEL protein to enable absolute quantification. Finally, when comparing results across multiple experimental batches, include inter-run calibrators and apply batch correction algorithms to minimize technical variation while preserving biological differences.