Recombinant Arabidopsis thaliana Probable inactive receptor kinase At5g53320 (At5g53320)

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Product Specs

Form
Lyophilized powder.
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Lead Time
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Notes
Avoid repeated freeze-thaw cycles. Store working aliquots at 4°C for up to one week.
Reconstitution
Centrifuge the vial briefly before opening to consolidate the contents. Reconstitute the protein in sterile, deionized water to a concentration of 0.1-1.0 mg/mL. For long-term storage, we recommend adding 5-50% glycerol (final concentration) and aliquoting at -20°C/-80°C. Our standard glycerol concentration is 50%, which can serve as a guideline.
Shelf Life
Shelf life depends on various factors, including storage conditions, buffer components, temperature, and protein stability. Generally, liquid formulations have a 6-month shelf life at -20°C/-80°C, while lyophilized formulations have a 12-month shelf life at -20°C/-80°C.
Storage Condition
Upon receipt, store at -20°C/-80°C. Aliquoting is essential for multiple uses. Avoid repeated freeze-thaw cycles.
Tag Info
Tag type is determined during the manufacturing process.
The tag type is determined during production. If you require a specific tag, please inform us, and we will prioritize its development.
Synonyms
At5g53320; K19E1.12; Probable inactive receptor kinase At5g53320
Buffer Before Lyophilization
Tris/PBS-based buffer, 6% Trehalose.
Datasheet
Please contact us to get it.
Expression Region
21-601
Protein Length
full length protein
Species
Arabidopsis thaliana (Mouse-ear cress)
Target Names
At5g53320
Target Protein Sequence
ETIKEDKHTLLQFVNNINHSHSLNWSPSLSICTKWTGVTCNSDHSSVDALHLAATGLRGD IELSIIARLSNLRFLILSSNNISGTFPTTLQALKNLTELKLDFNEFSGPLPSDLSSWERL QVLDLSNNRFNGSIPSSIGKLTLLHSLNLAYNKFSGEIPDLHIPGLKLLNLAHNNLTGTV PQSLQRFPLSAFVGNKVLAPVHSSLRKHTKHHNHVVLGIALSVCFAILALLAILLVIIIH NREEQRRSSKDKPSKRRKDSDPNVGEGDNKIVFFEGKNLVFDLEDLLRASAEVLGKGPFG TTYKVDLEDSATIVVKRIKEVSVPQREFEQQIENIGSIKHENVATLRGYFYSKDEKLVVY DYYEHGSLSTLLHGQKGLRDRKRLEWETRLNMVYGTARGVAHIHSQSGGKLVHGNIKSSN IFLNGKGYGCISGTGMATLMHSLPRHAVGYRAPEITDTRKGTQPSDVYSFGILIFEVLTG KSEVANLVRWVNSVVREEWTGEVFDEELLRCTQVEEEMVEMLQVGMVCTARLPEKRPNMI EVVRMVEEIRPEKLASGYRSEVSTGATTTPIGSLSGSPYIL
Uniprot No.

Target Background

Database Links

KEGG: ath:AT5G53320

STRING: 3702.AT5G53320.1

UniGene: At.43086

Protein Families
Protein kinase superfamily
Subcellular Location
Membrane; Single-pass membrane protein.

Q&A

What is At5g53320 and how is it classified within the Arabidopsis receptor kinase family?

At5g53320 is a Leucine-Rich Repeat Receptor-Like Kinase (LRR RLK) in Arabidopsis thaliana. It belongs to the large monophyletic group of Arabidopsis protein kinases that contain both transmembrane and cytoplasmic protein kinases . The LRR RLK family represents the largest RLK class in Arabidopsis with over 200 members, divided across 13 subfamilies (LRR I to XIII) classified according to the organization of LRRs in the extracellular domain . At5g53320 is part of a comprehensive set of LRR RLK Gateway-compatible constructs generated through NSF Arabidopsis 2010 project efforts .

What is the structural organization of At5g53320?

At5g53320 contains characteristic leucine-rich repeats (LRRs), which are tandem repeats of approximately 24 amino acids with conserved leucines in the extracellular domain . The protein contains a transmembrane domain and an intracellular kinase domain, typical of LRR RLKs. The "probable inactive" descriptor suggests that this receptor may have altered phosphorylation capabilities compared to active kinases, though it likely maintains structural roles in receptor complexes. The extracellular LRR domain is critical for protein-protein interactions and signal perception .

What recombinant tools are available for studying At5g53320?

Researchers have access to Gateway-compatible expression constructs for At5g53320. Specifically, the construct S5G53320BFF (stock number S5G53320BFF) is available through the Arabidopsis Biological Resource Center (ABRC) . This construct is a Gateway plant expression clone consisting of the coding region of At5g53320 cDNA in the vector pB35GWF. Expression of this clone in plants is driven by the CaMV35S promoter, and the transgenic LRR RLK includes a C-terminal Flag epitope tag for immunoprecipitation and Western analysis . This construct allows for heterologous expression and functional characterization in various experimental systems.

How can I design experiments to study At5g53320 function in Arabidopsis?

A comprehensive approach to studying At5g53320 function would include:

  • T-DNA insertion mutant analysis: T-DNA insertion lines disrupting At5g53320 expression are valuable tools. Search results mention T-DNA insertion lines (such as N556616) targeting At5g53320 . These can be used for reverse genetics approaches to assess loss-of-function phenotypes.

  • Expression analysis: Examine At5g53320 expression patterns across different tissues, developmental stages, and in response to various stimuli using techniques like qRT-PCR, RNA-seq, or reporter gene fusions.

  • Protein interaction studies: Utilize methods such as yeast two-hybrid, co-immunoprecipitation, or bimolecular fluorescence complementation to identify interacting partners.

  • Phenotypic assays: Subject mutant lines to various conditional phenotype assays to evaluate responses to environmental stimuli, hormones, and abiotic stresses .

  • Overexpression studies: Utilize the available Gateway expression clone S5G53320BFF to create overexpression lines and evaluate gain-of-function phenotypes .

What methodologies are effective for studying protein-protein interactions of At5g53320?

For studying physical interactions of At5g53320 with other proteins, particularly other LRR-RKs, researchers have employed several approaches:

  • Sensitized interaction assays: Comprehensive studies have tested reciprocal interactions among 200 of the 225 Arabidopsis LRR-RKs, creating a search space of 40,000 interactions . This approach identified both bidirectional (high-confidence) and unidirectional interactions.

  • Extracellular domain interaction analysis: Since the extracellular domains of LRR-RKs are involved in ligand perception and receptor complex formation, focusing on these domains can reveal important interaction partners .

  • Microplate reader-based techniques: Using tagged protein versions and appropriate controls, interactions can be quantitatively measured using microplate readers .

  • Statistical cut-offs: Apply stringent statistical criteria for identifying true interactions, such as requiring that interactions perform well in both bait-prey and prey-bait orientations to establish high-confidence bidirectional interactions .

How does At5g53320 function in plant signal transduction pathways?

LRR RLKs, including At5g53320, play roles in a wide variety of signal transduction pathways related to hormone responses and abiotic stress responses . While specific functions of At5g53320 require further characterization, research on related LRR RLKs provides insights into potential roles:

  • LRR RLKs can function as homo- or heterodimers, enhancing their signaling, sensing, and regulatory potential .

  • These receptors are involved in multiple developmental and environmental response pathways, allowing plants to perceive a wide range of signals .

  • The "probable inactive" designation suggests At5g53320 may function as a co-receptor or scaffold protein in receptor complexes, potentially modulating signaling without direct kinase activity.

  • Comprehensive studies of LRR RLK physical interactions have revealed complex networks of receptor interactions that impact both developmental and immune signaling decisions .

What phenotypes are associated with At5g53320 mutation or misexpression?

Based on the available search results, specific phenotypes for At5g53320 mutation can be analyzed in multiple contexts:

  • Root development: T-DNA insertion lines for At5g53320 have been screened for root developmental defects . The dataset from search result shows a code "R" for At5g53320 (N556616) in some conditions, which may indicate a root-related phenotype.

  • Hormone responses: LRR RLKs are involved in hormone perception and response pathways. Mutant analysis can reveal altered sensitivity to hormones like auxin, cytokinin, or brassinosteroids .

  • Abiotic stress responses: Testing At5g53320 mutants under various abiotic stress conditions (temperature, salinity, drought) can reveal roles in stress signaling .

  • Pathogen responses: Given the role of many LRR RLKs in immunity, investigating responses to various pathogens may reveal defense-related functions .

To systematically study these phenotypes, researchers should compare homozygous T-DNA insertion mutants with wild-type controls under various conditions, following established conditional phenotype assay protocols .

What are the optimal conditions for expressing recombinant At5g53320?

For expression of recombinant At5g53320 using the available Gateway construct (S5G53320BFF):

  • Bacterial expression: The plasmid can be maintained in E. coli DH5-alpha, grown in LB media at 37°C overnight with kanamycin selection .

  • Plant expression: The construct uses the constitutive CaMV 35S promoter for strong expression in plant tissues . Standard Arabidopsis transformation protocols (floral dip) can be used for stable transformation.

  • Protein extraction and detection: The C-terminal Flag epitope tag allows for immunoprecipitation and Western blot analysis using anti-Flag antibodies .

  • Subcellular localization: Consider using fluorescent protein fusions to visualize receptor localization, particularly at the plasma membrane where most LRR RLKs function.

How can I analyze interaction networks involving At5g53320?

To investigate the interaction network of At5g53320:

  • Comprehensive interaction mapping: Large-scale studies have mapped interactions between extracellular domains of LRR-RKs in Arabidopsis, providing a framework to position At5g53320 within this network .

  • Data analysis approaches:

    • High-confidence interactions require bidirectional verification (both bait-prey and prey-bait configurations)

    • Apply stringent statistical cut-offs to eliminate false positives

    • Consider both strong bidirectional interactions (567 in the reference dataset) and unidirectional interactions (2,586 in the reference dataset)

  • Integration with other datasets: Combine interaction data with expression data, phylogenetic relationships, and phenotypic information to build a comprehensive understanding of At5g53320 function.

Interaction TypeDefinitionNumber in Reference Dataset
Bidirectional InteractionsPassed statistical cut-off in both orientations567
Unidirectional InteractionsPassed statistical cut-off in only one orientation2,586

What are emerging approaches for studying At5g53320 function?

Emerging approaches that could advance our understanding of At5g53320 include:

  • CRISPR/Cas9 genome editing: Creating precise mutations in functional domains to dissect structure-function relationships.

  • Proximity labeling techniques: Using BioID or TurboID fusions to identify proteins in close proximity to At5g53320 in living cells.

  • Single-cell transcriptomics: Examining cell-type specific expression patterns and responses to stimuli.

  • Cryo-EM structural studies: Determining the three-dimensional structure of At5g53320 alone or in complex with interaction partners.

  • Phosphoproteomics: Identifying phosphorylation sites and potential substrates if At5g53320 retains some kinase activity despite being classified as "probable inactive."

How can computational approaches complement experimental studies of At5g53320?

Computational approaches offer powerful complements to experimental studies:

  • Homology modeling: Predicting the three-dimensional structure based on related proteins with known structures.

  • Molecular dynamics simulations: Investigating conformational changes upon ligand binding or protein-protein interactions.

  • Network analysis: Placing At5g53320 within the broader context of LRR RLK signaling networks by integrating multiple datasets.

  • Evolutionary analysis: Examining conservation and divergence of At5g53320 across plant species to infer functional importance of specific domains.

  • Machine learning approaches: Predicting potential interactors, functional partners, or biological processes based on existing datasets.

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