Recombinant Horse IL1A protein, His-tagged

• Cat.No.: IL1A-623H
• Product Overview: Recombinant Horse IL1A aa. (Asp95~Gln269 (Accession # Q28385)) fused with N-terminal His tag was produced in E. coli cells.

Specification

• Source: E. coli
• Species: Horse
• Tag: His
• Form: Freeze-dried powder
• Molecular Mass: Predicted Molecular Mass: 21.5kDa
• Protein length: Asp95~Gln269 (Accession # Q28385)
• Endotoxin: <1.0EU per 1µg (determined by the LAL method)
• Purity: >95%
• Characteristic: The isoelectric point is 6.
• Applications: SDS-PAGE; WB; ELISA; IP.
• Stability: The thermal stability is described by the loss rate. The loss rate was determined by accelerated thermal degradation test, that is, incubate the protein at 37°C for 48h, and no obvious degradation and precipitation were observed. The loss rate is less than 5% within the expiration date under appropriate storage condition.
• Storage: Avoid repeated freeze/thaw cycles. Store at 2-8°C for one month. Aliquot and store at -80°C for 12 months.
• Storage buffer: Supplied as lyophilized form in PBS, pH 7.4, containing 5% sucrose, 0.01% sarcosyl.
• Reconstitution: Reconstitute in sterile PBS, pH7.2-pH7.4.

Gene Information

• Gene Name: IL1A interleukin 1 alpha [ Equus caballus (horse) ]
• Official Symbol: IL1A
• Synonyms: IL1A; interleukin-1 alpha; IL-1 alpha
• Gene ID: 100064969
• mRNA Refseq: NM_001082500.2
• Protein Refseq: NP_001075969.2
• UniProt ID: Q28385

Reviews

04/08/2021

High solubility.

07/02/2020

Good for intracellular staining.

03/13/2019

Effective in apoptosis assays.

Q&As

What methods are employed to dissect the intricate cross-talk between IL-1α and other cytokines, shedding light on its role in immune modulation?

Cross-talk between IL-1α's and other cytokines is dissected through methods such as co-immunoprecipitation, ELISA, and cytokine profiling arrays.

What experimental approaches allow researchers to dissect the paradoxical roles of IL-1α as both a pro-inflammatory and tissue repair mediator in distinct contexts?

IL-1α's paradoxical roles are dissected using conditional knockout mice, 3D culture systems, and molecular analyses to delineate context-specific effects.

How are cutting-edge techniques like single-cell RNA sequencing utilized to unravel the heterogeneity in IL-1α-responsive cell populations and their functional implications?

Single-cell RNA sequencing uncovers heterogeneity in IL-1α-responsive cell populations and their roles, revealing distinct molecular profiles and functions.

How is the intricate web of IL-1α's pro-inflammatory signaling pathways decoded using advanced experimental techniques?

IL-1α's intricate pro-inflammatory signaling pathways are decoded using advanced techniques like mass spectrometry, phosphoproteomics, and bioinformatics.

How are state-of-the-art genetic editing tools such as CRISPR-Cas9 applied to unravel IL-1α's precise contributions to inflammatory diseases?

Genetic editing tools like CRISPR-Cas9 unveil IL-1α's contributions to diseases by generating knockout models and studying resulting phenotypic changes.

How do researchers manipulate in vitro co-culture systems to dissect the dynamic interplay between immune cells and stromal cells in IL-1α-mediated responses?

In vitro co-culture systems are manipulated to study IL-1α-mediated responses, elucidating immune-stromal cell interactions via cytokine-specific neutralization.

What experimental strategies enable the identification of specific cellular receptors and downstream effectors responsible for IL-1α's diverse physiological effects?

Specific cellular receptors and effectors influenced by IL-1α are identified through techniques like co-immunoprecipitation, ChIP-seq, and siRNA knockdown.

How are sophisticated imaging techniques like live-cell microscopy harnessed to capture the real-time dynamics of IL-1α release and its impact on neighboring cells?

Live-cell microscopy captures real-time IL-1α release dynamics and its impact on neighboring cells, facilitated by fluorescent tagging and high-resolution imaging.

How is the quantitative relationship between IL-1α levels and disease progression established through longitudinal studies and statistical modeling?

Longitudinal studies and statistical modeling establish the quantitative relationship between IL-1α levels and disease progression, offering predictive insights.

How do multi-omics analyses, including transcriptomics and proteomics, provide a holistic view of the network of molecules influenced by IL-1α signaling?

Multi-omics analyses provide a holistic view of IL-1α signaling's impact, integrating transcriptomics, proteomics, and metabolomics data for comprehensive insights.