Recombinant Arabidopsis thaliana Kelch repeat-containing protein At3g27220 (At3g27220)

What is the Kelch repeat-containing protein At3g27220?

The Kelch repeat-containing protein At3g27220 is a protein encoded by the At3g27220 locus in the Arabidopsis thaliana genome. According to available information, it is characterized as a protein containing Kelch repeat domains, which are typically involved in protein-protein interactions. The protein is also known by its ORF name K17E12.4 and has a UniProt accession number of Q9LK31 . Kelch repeat domains are characterized by a β-propeller structure that provides a platform for protein-protein interactions, suggesting that At3g27220 may function in cellular processes requiring specific protein recognition and binding. These domains are often found in proteins involved in cytoskeletal organization, gene expression regulation, and various signaling pathways in plant cells. The full-length protein sequence consists of 426 amino acids with multiple predicted functional domains that may contribute to its biological role in plant cellular processes.

What is the amino acid sequence and structural characterization of At3g27220?

The amino acid sequence of the Kelch repeat-containing protein At3g27220 is as follows: "MANKPDHHHHHHQSSRRLMLVLYFTSV LGIAGFIAAFLCLSSSIPSVSAVFSIWVPVNRPEIQIPIIDSKIVQKRSKQSNDTKDHVRFLSAIFADIPAPELKWE EMESAPVPRLDGYSVQINNLLYVFSGYGSLDYVHSHVDVFNFTDNKWCDRFHTPKEMANSH LGIVTDGRYVYVVSGQLGPQCRGPTSRSFVLDSFTKTWLEFPSLPAPRYAPATQIWRGRLH VMGGSKENRNAVAFDNWSIAVKDGKALDEWREEVPIPRGGPHRACVVANDKLLVIGGQE GDFMAKPNSPIFKCSRRREIFNGEVYMMDEEMKWKMLPPMPKNNSHIESAWIIVNNSIVI VGGTTDWHPVTKRLVLVGEIFRFQLDTLTWSVIGRLPYRVKTAMAGFWNGYLYFTSGQR DRGPDNPQPGKVIGEMWRTKLKF" . Structural analysis reveals the presence of multiple Kelch repeat motifs, which typically form a β-propeller structure. Each Kelch repeat consists of about 50 amino acids forming a four-stranded β-sheet. These repeated units are arranged radially around a central axis, creating a structure resembling a propeller blade. This conformation creates multiple potential binding interfaces that can interact with different protein partners. Computational structural predictions suggest that At3g27220 likely exhibits the characteristic β-propeller architecture with multiple binding pockets that may accommodate different interaction partners in plant cellular contexts.

Where is At3g27220 expressed in Arabidopsis thaliana?

The expression pattern of At3g27220 across different tissues and developmental stages of Arabidopsis thaliana provides important insights into its potential biological functions. While specific expression data for At3g27220 is limited in the provided search results, research approaches to determine expression patterns typically include RNA-seq analysis, quantitative PCR (qPCR), and promoter-reporter fusion studies. Based on general methodologies in Arabidopsis research, expression analysis would involve extraction of RNA from different tissues (roots, leaves, stems, flowers, and siliques) and at various developmental stages, followed by reverse transcription and quantification. The expression region is reported as 1-426 , suggesting the full-length protein is expressed. Researchers investigating this protein would likely utilize publicly available transcriptome datasets, such as those from the Arabidopsis Information Resource (TAIR) or the Bio-Analytic Resource for Plant Biology (BAR), to examine expression patterns across tissues, developmental stages, and in response to various stimuli. This information would be crucial for understanding the spatiotemporal regulation of At3g27220 and formulating hypotheses about its biological roles.

How is At3g27220 related to other Kelch repeat proteins?

Phylogenetic analysis of At3g27220 in relation to other Kelch repeat-containing proteins provides valuable evolutionary context. The Kelch repeat domain is highly conserved across plant species, suggesting important functional roles that have been maintained throughout evolutionary history. Comparison of At3g27220 with other Kelch repeat proteins in Arabidopsis and in other plant species would typically involve multiple sequence alignment using tools such as MUSCLE or CLUSTALW, followed by phylogenetic tree construction using maximum likelihood or Bayesian methods. These analyses would help identify closely related proteins that might share functional similarities with At3g27220. Researchers would also examine synteny and gene duplication events to understand the evolutionary history of this gene. Conservation analysis of specific amino acid residues within the Kelch repeats could highlight functionally critical regions of the protein. This evolutionary perspective is essential for predicting the functional roles of At3g27220 based on better-characterized homologs and for understanding how this protein family has diversified to perform specialized functions in plant biology.

What are the optimal expression and purification methods for recombinant At3g27220?

For optimal expression and purification of recombinant At3g27220, researchers should consider several methodological approaches. Expression systems for plant proteins like At3g27220 typically include bacterial (E. coli), yeast (P. pastoris), insect cell (baculovirus), or plant-based expression systems. Based on available product information, recombinant At3g27220 has been successfully produced with a polyhistidine tag (HHHHHH), which facilitates purification via immobilized metal affinity chromatography (IMAC) . For purification, a multi-step protocol is recommended: 1) Initial capture using Ni-NTA affinity chromatography; 2) Intermediate purification using ion exchange chromatography; 3) Polishing step with size exclusion chromatography to achieve high purity. Optimized buffer conditions include a Tris-based buffer with 50% glycerol for protein stability . For storage, it is advised to maintain the protein at -20°C for routine use or at -80°C for extended storage periods, with a caution against repeated freeze-thaw cycles . Working aliquots should be stored at 4°C and used within one week to maintain protein activity. These methodological considerations are crucial for obtaining properly folded, functional protein for downstream structural and functional analyses.

How can researchers analyze protein-protein interactions involving At3g27220?

Analysis of protein-protein interactions involving At3g27220 requires sophisticated methodological approaches due to the protein's multiple Kelch repeat domains, which likely mediate diverse interaction networks. Researchers should employ complementary techniques to identify and validate interaction partners. Yeast two-hybrid (Y2H) screening offers a high-throughput approach to identify potential interactors from an Arabidopsis cDNA library. For in vitro validation, pull-down assays using purified recombinant At3g27220 as bait can confirm direct interactions. Co-immunoprecipitation (Co-IP) followed by mass spectrometry represents the gold standard for identifying physiologically relevant interactions in plant tissues. Bimolecular fluorescence complementation (BiFC) or Förster resonance energy transfer (FRET) microscopy can visualize interactions in living plant cells, providing spatial information about where these interactions occur. For network-level understanding, researchers should apply co-expression network analysis similar to those described for other Arabidopsis proteins . This approach reveals genes with correlated expression patterns that may function in the same biological pathways. Differential network analysis comparing control and experimental conditions can reveal condition-specific interactions, as exemplified by other Arabidopsis studies showing network reconfiguration during biotic stress responses .

What experimental approaches can determine the biological function of At3g27220?

Determining the biological function of At3g27220 requires a comprehensive experimental approach combining genetic, molecular, and biochemical techniques. CRISPR-Cas9 gene editing or T-DNA insertion lines should be used to generate knockout mutants, while controlled overexpression lines can reveal gain-of-function phenotypes. Phenotypic characterization should include detailed morphological analysis across developmental stages and stress conditions, as Kelch proteins often function in stress responses. RNA-seq analysis comparing wild-type and mutant plants would identify genes with altered expression, revealing potential regulatory networks. This approach has proven valuable in studying transcriptional responses in Arabidopsis under various conditions . Subcellular localization studies using fluorescent protein fusions would determine where At3g27220 functions within the cell. For biochemical characterization, researchers should investigate potential enzymatic activities or substrate binding properties. Given that other Kelch proteins may function in hypoxia responses and defense mechanisms , researchers should examine At3g27220 mutants under these specific stress conditions. The protein's role in plant-microbe interactions could be assessed by challenging mutant plants with beneficial fungi like Trichoderma species, which are known to alter the transcriptional landscape of Arabidopsis .

How does At3g27220 expression respond to environmental stresses?

Investigation of At3g27220 expression patterns under various environmental stresses requires systematic experimental design and precise quantification methods. Researchers should expose Arabidopsis plants to a range of abiotic stresses (drought, salt, cold, heat, hypoxia) and biotic stresses (bacterial, fungal, and insect challenges) in controlled time-course experiments. Gene expression analysis using RT-qPCR with gene-specific primers would provide accurate quantification of transcript levels across these conditions. RNA-seq analysis offers a more comprehensive approach, placing At3g27220 expression changes in the context of global transcriptome reprogramming. Based on research on other Arabidopsis genes, transcription factors like those in the AP2/ERF family may regulate At3g27220 expression under stress conditions . Promoter analysis using in silico tools would identify potential regulatory elements in the At3g27220 promoter, such as the GCC-box associated with pathogenesis . Reporter gene fusions (promoter::GUS or promoter::LUC) would enable visualization of spatial and temporal expression patterns in planta under different stresses. These methodologies would reveal whether At3g27220 participates in specific stress response pathways, similar to other plant proteins involved in both hypoxia and defense mechanisms .

What co-expression network analysis approaches are suitable for studying At3g27220?

Co-expression network analysis provides powerful insights into the functional context of At3g27220 by identifying genes with similar expression patterns across various conditions. Researchers should implement weighted gene co-expression network analysis (WGCNA) using RNA-seq data from diverse tissues and stress conditions. This methodology has successfully revealed functional gene modules in Arabidopsis in previous studies . Construction of condition-specific networks (control versus stress conditions) can highlight how At3g27220 interactions change in response to environmental perturbations. Differential network analysis comparing normal and stressed conditions, as demonstrated in previous Arabidopsis-fungal interaction studies, would reveal topological changes in gene associations . Previous research has shown that interaction networks under stress conditions may have fewer edges but higher correlation values compared to control networks, indicating more specific and robust gene associations during stress responses . Network metrics including edge density, node connectivity, and correlation strength should be calculated to characterize network properties. Identification of hub genes connected to At3g27220 would highlight key regulators within the network. Researchers should also perform GO enrichment analysis on co-expressed gene modules to identify overrepresented biological processes, as demonstrated in previous Arabidopsis studies examining processes like camalexin metabolism, hormone signaling, and defense responses .

What storage and handling protocols optimize At3g27220 protein stability?

Optimal storage and handling of purified recombinant At3g27220 protein is critical for maintaining its structural integrity and biological activity. According to product specifications, the protein should be stored in a Tris-based buffer supplemented with 50% glycerol, which has been optimized specifically for this protein . For short-term storage (up to one week), the protein can be maintained at 4°C as working aliquots. For medium-term storage, -20°C is recommended, while extended storage periods require -80°C conditions . To prevent protein degradation, researchers should strictly avoid repeated freeze-thaw cycles, as this can lead to protein denaturation and loss of activity . When working with the protein, all buffers should be pre-chilled and handling should be done on ice to minimize thermal denaturation. For analytical experiments requiring high protein stability, addition of protease inhibitors is recommended. Researchers should also consider testing different buffer compositions (varying pH, salt concentration, and additives) to identify optimal conditions for specific experimental applications. Dynamic light scattering (DLS) or size exclusion chromatography can be used to monitor protein aggregation state during storage. These careful handling procedures are essential for ensuring that experimental results accurately reflect the protein's native properties and are not artifacts of improper storage conditions.

How should researchers design experiments to study At3g27220 in defense mechanisms?

Designing robust experiments to investigate At3g27220's potential role in plant defense mechanisms requires careful consideration of biotic challenges, genetic resources, and analytical methods. Researchers should establish a comprehensive experimental system using wild-type, knockout, and overexpression Arabidopsis lines to elucidate At3g27220 function. Plant materials should be challenged with diverse pathogens including bacteria (Pseudomonas syringae), fungi (Botrytis cinerea, Trichoderma species), and oomycetes (Hyaloperonospora arabidopsidis) to assess pathogen-specific responses. Previous research has shown that Arabidopsis exhibits distinct transcriptional responses during interactions with beneficial fungi like Trichoderma atroviride and Trichoderma virens, including differential expression of defense-related genes . Time-course experiments are crucial, as defense responses typically show dynamic temporal patterns, with sampling at key timepoints (e.g., 48, 72, and
96 hours post-inoculation) as demonstrated in previous Arabidopsis-Trichoderma interaction studies . Molecular analyses should include quantification of defense hormones (salicylic acid, jasmonic acid, ethylene), expression analysis of key defense marker genes, and measurement of antimicrobial compounds like camalexin, which has been shown to be differentially regulated during plant-microbe interactions . Researchers should also investigate potential connections between defense mechanisms and hypoxia responses, as previous studies have identified transcription factors with dual roles in these processes .

What methodological approaches can resolve contradictory findings in At3g27220 studies?

Resolving contradictory findings in At3g27220 research requires rigorous methodological approaches that address experimental variability and biological complexity. Researchers should first conduct a systematic meta-analysis of existing literature to identify specific contradictions and their potential sources. Standardization of experimental conditions is critical, including growth conditions (light intensity, photoperiod, temperature, humidity), plant developmental stage, and stress treatment protocols. Genetic background effects should be controlled by using multiple independent mutant or transgenic lines in the same ecotype background. For protein-protein interaction studies showing conflicting results, researchers should employ multiple complementary techniques (Y2H, BiFC, Co-IP, FRET) to validate interactions under physiologically relevant conditions. Contradictory gene expression results can be resolved through absolute quantification methods like digital PCR in addition to relative quantification by qPCR. When analyzing plant phenotypes, high-throughput phenomics approaches with automated image analysis can provide objective, quantitative measurements that reduce observer bias. Statistical analysis should include rigorous power calculations to ensure adequate sample sizes and appropriate statistical tests for the data structure. Multi-laboratory validation studies, where identical experiments are performed in different research environments, can distinguish robust findings from lab-specific artifacts. These methodological considerations will help establish consensus on At3g27220 function despite initial contradictory results.

What bioinformatic tools are most effective for predicting At3g27220 function?

For comprehensive functional prediction of At3g27220, researchers should utilize an integrated bioinformatic approach combining multiple computational tools and databases. Sequence-based function prediction should begin with InterPro and Pfam database searches to identify conserved domains, particularly focusing on the Kelch repeat domains that characterize this protein. Structural prediction using AlphaFold2 or I-TASSER would generate three-dimensional models of At3g27220, revealing the likely β-propeller conformation typical of Kelch repeat proteins and potential binding sites. Protein-protein interaction predictions using STRING or MINT databases would identify potential functional partners, while integration with experimental proteomics data would strengthen these predictions. For metabolic pathway involvement, researchers should use KEGG or PlantCyc to identify potential biochemical pathways associated with the protein. Gene co-expression analysis using tools like ATTED-II specifically for Arabidopsis would identify genes with similar expression patterns across multiple conditions, suggesting functional relationships. This approach has proven valuable in previous studies that identified functional gene modules in Arabidopsis response to fungi . Gene Ontology (GO) term enrichment analysis of these co-expressed genes would reveal biological processes potentially associated with At3g27220. Researchers should also perform comparative genomics analysis across plant species to identify conserved synteny and co-evolution patterns. These diverse bioinformatic approaches would collectively provide a multifaceted prediction of At3g27220 function that can guide experimental validation.

How can researchers analyze differential expression of At3g27220 across experimental conditions?

Robust analysis of At3g27220 differential expression requires careful experimental design and sophisticated statistical approaches. Researchers should design experiments with sufficient biological replicates (minimum n=3, preferably n≥5) to account for biological variability. RNA extraction procedures should be standardized across all samples to minimize technical variation. For RNA-seq analysis, researchers should follow established pipelines including quality control checks (ensuring Phred scores >30), read mapping to the Arabidopsis reference genome (expecting >95% mapping rate), and differential expression analysis using DESeq2 or edgeR . These tools implement negative binomial models appropriate for count data and provide adjusted p-values that control for multiple testing. For RT-qPCR validation, researchers should select stable reference genes verified under the specific experimental conditions and use the ΔΔCt method with appropriate PCR efficiency corrections. Visualization of expression data should include both volcano plots highlighting statistical significance versus fold change and heat maps showing expression patterns across conditions. When analyzing At3g27220 expression in the context of stress responses, researchers should compare its regulation to known stress-responsive genes, similar to approaches used in Arabidopsis-Trichoderma interaction studies that examined defense-related genes . Time-course experiments require more complex statistical models that account for temporal dependencies, such as those implemented in the maSigPro R package. These analytical approaches ensure robust identification of significant expression changes in At3g27220 across experimental conditions.

What statistical methods best analyze At3g27220 protein-protein interaction data?

Analysis of protein-protein interaction data for At3g27220 requires specialized statistical methods that account for the unique characteristics of interaction networks. For high-throughput Y2H or mass spectrometry-based interactome studies, researchers should implement stringent filtering to control false discovery rates, typically using statistical methods like SAINT (Significance Analysis of INTeractome) that model true and false interactions based on spectral counts. Network analysis of At3g27220 interactions should include calculation of topological parameters such as degree centrality, betweenness centrality, and clustering coefficients to identify the protein's position within the global interactome. Previous studies examining Arabidopsis interaction networks have shown that networks undergo significant topological reconfiguration under stress conditions, with changes in edge density and correlation strength . Researchers should perform differential network analysis comparing interaction patterns across conditions, as demonstrated in previous studies comparing Arabidopsis networks under control and fungal interaction conditions . Enrichment analysis of interaction partners should utilize hypergeometric tests to identify overrepresented functional categories, cellular compartments, or pathways. For co-expression network analysis, weighted approaches like WGCNA are recommended, with careful selection of the soft thresholding power parameter to achieve scale-free topology. Visualization of network data should use force-directed layouts to reveal natural clusters of functionally related proteins. These statistical approaches collectively provide rigorous analysis of At3g27220's position within the plant interactome and its potential functional associations.