Recombinant Arabidopsis thaliana Vacuolar iron transporter homolog 1 (At1g21140)

What is the structural characterization of Arabidopsis thaliana Vacuolar iron transporter homolog 1?

The Vacuolar iron transporter homolog 1 (At1g21140) is a membrane protein in Arabidopsis thaliana, also known as Protein NODULIN-LIKE 1. Its structure consists of 200 amino acids with the full sequence: MESHNVSNSLNLDMEMDQEKAFDYSKRAQWLRAAVLGANDGLVSTASLMMGVGAVKQDVKVMILSGFAGLVAGACSMAIGEFVSVYSQYDIEVAQMKRENGGQVEKEKLPSPMQAAAASALAFSLGAIVPLMAAAFVKDYHVRIGAIVAAVTLALVMFGWLGAVLGKAPVFKSSARVLIGGWLAMAVTFGLTKLIGTHSL .

The protein contains multiple transmembrane domains that facilitate its function in iron transport across cellular membranes. Its UniProt accession number is Q9LPU9, and it's encoded by the gene At1g21140 (also identified by ORF name T22I11.3) . This transporter belongs to the Vacuolar Iron Transporter (VIT) family, whose members typically function in exporting iron from the cytoplasm into vacuoles, playing crucial roles in iron homeostasis mechanisms .

What expression patterns does At1g21140 exhibit in different plant tissues?

At1g21140 shows differential expression across Arabidopsis tissues, with expression patterns that provide important clues about its physiological functions. While specific expression data for At1g21140 is not directly provided in the search results, research on related VIT family proteins indicates tissue-specific expression patterns.

Studies of VIT family members in soybean, for instance, show that certain homologs (GmVTL1 and GmVTL2) have significantly higher expression in nodules compared to other tissues . By extension, At1g21140 may also exhibit tissue-specific expression patterns that correlate with iron transport needs in different parts of the plant.

Researchers investigating At1g21140 expression should consider:

• Using quantitative PCR to measure transcript levels across different tissues

• Employing promoter-reporter constructs to visualize spatial expression patterns

• Analyzing publicly available transcriptome datasets to compare expression under various conditions

• Conducting in situ hybridization for high-resolution localization studies

How is the recombinant At1g21140 protein properly stored and handled?

Proper storage and handling of recombinant At1g21140 protein is essential for maintaining its structural integrity and biological activity. The protein should be stored in a Tris-based buffer with 50% glycerol that has been optimized specifically for this protein .

For short-term storage, keep working aliquots at 4°C for up to one week. For long-term storage, store the protein at -20°C, or preferably at -80°C for extended periods . It is crucial to avoid repeated freeze-thaw cycles as this can significantly compromise protein quality and activity .

When working with the protein, consider these handling recommendations:

• Thaw aliquots gently on ice

• Prepare small working aliquots to minimize freeze-thaw events

• Use appropriate buffer conditions when designing experiments

• Consider protein stability when planning the timeline for experimental procedures

What are the optimal conditions for expressing recombinant At1g21140 in heterologous systems?

Successful expression of recombinant At1g21140 requires careful optimization of expression systems and conditions. While the search results don't provide specific details about expression systems for At1g21140, general approaches for membrane proteins like this vacuolar iron transporter can be adapted.

For bacterial expression systems:

• Use E. coli strains optimized for membrane protein expression (e.g., C41(DE3), C43(DE3))

• Consider lower induction temperatures (16-20°C) to improve proper folding

• Employ fusion tags that enhance solubility (e.g., MBP, SUMO)

• Optimize induction parameters (IPTG concentration, induction time)

For eukaryotic expression systems:

• Yeast systems like Pichia pastoris may provide better membrane protein folding

• Plant-based expression systems might maintain native post-translational modifications

• Insect cell expression using baculovirus can yield higher amounts of functional protein

The specific tag used for the recombinant At1g21140 protein mentioned in the search results will be determined during the production process , suggesting that tag optimization is an important consideration for successful expression and purification.

What methodologies are most effective for studying iron transport activity of At1g21140?

Investigating the iron transport activity of At1g21140 requires specialized techniques that can directly measure transport function or assess iron accumulation patterns. Based on studies of related transporters in the VIT family, several approaches can be applied:

• Heterologous Expression Systems:

  • Yeast complementation assays using iron transport-deficient strains

  • Xenopus oocyte expression followed by radioactive iron uptake measurements

  • Liposome reconstitution with purified protein for direct transport measurements

• Plant-Based Functional Analysis:

  • Comparison of iron content in vacuoles isolated from wild-type and knockout/overexpression lines

  • Use of iron-specific fluorescent probes to track iron movement in living cells

  • Synchrotron X-ray fluorescence microscopy for high-resolution iron localization

• Biochemical Characterization:

  • Transport kinetics determination (Km, Vmax values for iron)

  • Assessment of substrate specificity (testing other metals)

  • Identification of critical residues through site-directed mutagenesis

Given that members of the VIT family export iron from the cytoplasm into vacuoles , assays should be designed to detect this directional transport activity.

How can QTL mapping approaches be applied to study At1g21140 function in Arabidopsis?

QTL mapping represents a powerful approach to understanding the function of At1g21140 in relation to iron homeostasis and plant phenotypes. Based on methodologies described in the search results:

• Development of Appropriate Mapping Populations:

  • Create STepped Aligned Recombinant Inbred Strains (STAIRS) that differ in the region containing At1g21140

  • Develop Chromosome Substitution Strains (CSSs) where chromosome segments containing At1g21140 are exchanged between ecotypes

  • Generate narrow STAIRS through marker-assisted backcrossing to achieve higher mapping resolution

• Phenotypic Evaluation:

  • Measure iron content in various tissues

  • Assess tolerance to iron deficiency or excess

  • Analyze growth parameters under controlled iron conditions

  • Examine flowering time and other developmental traits that might be affected by iron homeostasis

• Genotyping and Statistical Analysis:

  • Use polymorphic microsatellite markers to genotype the mapping population

  • Conduct ANOVA and model fitting to identify significant QTL

  • Calculate Pearson's correlation coefficients between traits to identify pleiotropic effects

  • Search for candidate genes within mapped regions to identify At1g21140 and related genes

This approach has proven successful in mapping QTL for flowering time in Arabidopsis with high resolution (2-3 cM) , and similar strategies could be applied to traits associated with iron transport and At1g21140 function.

How do post-translational modifications affect At1g21140 function and regulation?

Post-translational modifications (PTMs) likely play significant roles in regulating At1g21140 function, though specific details are not provided in the search results. Based on knowledge of membrane transporters and iron homeostasis mechanisms:

Researchers should consider investigating:

• Phosphorylation:

  • Identify potential phosphorylation sites using prediction tools

  • Perform phosphoproteomic analysis under various iron conditions

  • Create phosphomimetic and phospho-null mutants to assess functional changes

  • Investigate kinases and phosphatases involved in the regulation

• Ubiquitination and Protein Turnover:

  • Examine protein stability under different iron conditions

  • Assess ubiquitination patterns and their correlation with protein degradation

  • Identify E3 ligases potentially involved in At1g21140 regulation

• Other PTMs:

  • Investigate S-nitrosylation, which often affects metal transporters

  • Examine glycosylation patterns if present

  • Consider redox-based modifications that might respond to iron-induced oxidative stress

A methodological approach combining mass spectrometry, site-directed mutagenesis, and functional assays would be most effective for characterizing the PTM landscape of At1g21140 and understanding its regulatory implications.

What protein-protein interactions are critical for At1g21140 function?

Understanding the interactome of At1g21140 is essential for elucidating its functional mechanisms and regulatory networks. While specific interaction partners are not detailed in the search results, several approaches can be employed to identify and characterize these interactions:

• High-throughput Screening Methods:

  • Yeast two-hybrid (Y2H) screening with membrane-specific adaptations

  • Split-ubiquitin membrane Y2H for membrane protein interactions

  • Co-immunoprecipitation coupled with mass spectrometry (Co-IP-MS)

  • Proximity-dependent biotin identification (BioID) in planta

• Validation and Characterization Techniques:

  • Bimolecular fluorescence complementation (BiFC) to visualize interactions in vivo

  • Förster resonance energy transfer (FRET) to measure interaction dynamics

  • Co-localization studies using fluorescent protein fusions

  • Pull-down assays with recombinant proteins to confirm direct interactions

• Functional Relevance Assessment:

  • Analyze iron transport activity in the presence/absence of interaction partners

  • Examine phenotypes of mutants lacking key interaction partners

  • Investigate conditional interactions dependent on iron status

Based on studies of related transporters, potential interaction partners might include chaperones, regulatory proteins responding to iron status, vesicular trafficking components, and other membrane transporters involved in iron homeostasis.

How does At1g21140 function compare across different plant species and iron transport systems?

Comparative analysis of At1g21140 homologs across plant species provides valuable insights into evolutionary conservation and functional adaptations of vacuolar iron transporters. From the search results, we can draw parallels to related transporters:

• Homology and Functional Conservation:

  • Soybean homologs GmVTL1 and GmVTL2 show high expression in nodules and are implicated in iron transport

  • The VIT family generally functions in exporting iron from the cytoplasm into vacuoles

  • Nodulin-21 and SEN1 are proposed as candidates for iron uptake into the symbiosome

• Methodological Approaches for Comparative Studies:

  • Phylogenetic analysis of VIT family members across plant species

  • Complementation studies using heterologous expression in yeast or plants

  • Domain swapping experiments to identify functionally conserved regions

  • Transcriptome comparisons across species under various iron conditions

• Specialized Functions in Different Plant Groups:

  • Investigation of tissue-specific expression patterns

  • Assessment of iron transport kinetics in homologs from different species

  • Analysis of regulatory elements in promoter regions

A detailed comparative analysis could be presented in table format:

What are common challenges in purifying recombinant At1g21140 and how can they be addressed?

Purifying membrane proteins like At1g21140 presents specific challenges due to their hydrophobic nature and requirement for a lipid environment. Based on general membrane protein purification principles and the limited information from search result :

• Solubilization Challenges:

  • Challenge: Insufficient extraction from membranes

  • Solution: Optimize detergent type, concentration, and solubilization conditions

  • Approach: Screen detergents (DDM, LMNG, CHAPS) at various concentrations and temperatures

• Protein Stability Issues:

  • Challenge: Rapid degradation or aggregation during purification

  • Solution: Include protease inhibitors, optimize buffer conditions, and maintain cold temperatures

  • Approach: Add glycerol (as mentioned in the storage buffer for At1g21140 ), stabilizing agents, and consider amphipols for final stages

• Purification Yield:

  • Challenge: Low expression and recovery of functional protein

  • Solution: Optimize expression systems and purification protocols

  • Approach: Consider fusion tags that enhance solubility and yield; optimize affinity chromatography conditions

• Maintaining Activity:

  • Challenge: Loss of transport activity during purification

  • Solution: Validate function at each purification step

  • Approach: Develop activity assays that can be performed with partially purified protein

The recombinant At1g21140 described in search result is stored in a Tris-based buffer with 50% glycerol, suggesting this composition helps maintain protein stability. This information can guide researchers in developing appropriate purification and storage protocols.

How can transcriptome analysis be effectively used to study At1g21140 function in iron homeostasis?

Transcriptome analysis provides powerful insights into the regulatory networks and functional context of At1g21140. Based on the approaches mentioned in search result and standard transcriptomic methodologies:

• Experimental Design Considerations:

  • Compare gene expression between wild-type and At1g21140 knockout/overexpression lines

  • Examine transcriptional changes under varying iron conditions (deficiency, sufficiency, excess)

  • Analyze expression at different developmental stages and in different tissues

  • Consider both chronological and physiological age points for comparison

• Technical Approaches:

  • RNA-Seq for genome-wide expression profiling

  • Microarray analysis as mentioned in studies of QTL

  • qRT-PCR validation of key differentially expressed genes

  • Single-cell RNA-Seq for cell-type specific responses

• Data Analysis Strategies:

  • Gene Ontology (GO) enrichment analysis to identify affected biological processes

  • Gene Set Enrichment Analysis (GSEA) to detect subtle but coordinated changes

  • Co-expression network analysis to identify genes functioning with At1g21140

  • Integration with publicly available datasets for comparative analysis

• Validation and Follow-up Studies:

  • Confirmatory qPCR for selected genes

  • Promoter analysis of co-regulated genes

  • Protein-level validation using proteomics

  • Genetic interaction studies with identified network components

Transcriptome analyses of soybean have identified GmVTL1 and GmVTL2 (VIT family members) as having significantly higher expression in nodules compared to other VIT family members , demonstrating how transcriptomics can reveal tissue-specific roles of iron transporters.

What statistical approaches are most appropriate for analyzing phenotypic data in At1g21140 functional studies?

Selecting appropriate statistical methods is crucial for rigorous interpretation of phenotypic data in At1g21140 studies. Based on the approaches described in search results:

• Descriptive Statistics:

  • Measures of central tendency (mean, median, mode) to summarize phenotypic data

  • Variability measures (range, variance, standard deviation) to assess data dispersion

  • Graphical representations through tables and graphs for data visualization

• Inferential Statistics for Hypothesis Testing:

  • Formulation of null and alternative hypotheses regarding At1g21140 function

  • Selection of appropriate statistical tests based on data distribution and experimental design

  • Consideration of Type I and Type II errors in statistical decision-making

  • Evaluation of statistical power to detect biologically meaningful effects

• Advanced Statistical Methods for QTL Analysis:

  • ANOVA for detecting significant differences between genotypes

  • Least Squares Model Fitting to identify and characterize QTL

  • Pearson's Correlation Coefficients to examine relationships between traits

  • Parameter estimation for QTL effects, including gene action and pleiotropic effects

• Considerations for Experimental Design:

  • Control of variability through standardized procedures

  • Selection of reliable dependent variables and appropriate sample sizes

  • Implementation of randomization and blocking to control for extraneous variables

A decision tree approach can be useful for selecting the appropriate statistical analysis based on experimental design, data characteristics, and research questions .

How might CRISPR/Cas9 gene editing advance our understanding of At1g21140 function?

CRISPR/Cas9 technology offers unprecedented opportunities for precise genetic manipulation to study At1g21140 function. While not directly mentioned in the search results, this cutting-edge approach can be applied in several ways:

• Targeted Gene Modifications:

  • Generate complete knockout mutants through frameshift mutations

  • Create specific amino acid substitutions to study structure-function relationships

  • Introduce tags for protein visualization and purification without affecting function

  • Develop conditional knockouts using inducible CRISPR systems

• Promoter Editing:

  • Modify regulatory elements to alter expression patterns

  • Create reporter fusions at the endogenous locus

  • Implement synthetic promoters for controlled expression studies

• Methodological Approaches:

  • Design multiple guide RNAs targeting different regions of At1g21140

  • Use homology-directed repair for precise modifications

  • Implement base editing or prime editing for specific nucleotide changes

  • Screen edited plants using a combination of PCR-based genotyping and sequencing

• Applications for Functional Genomics:

  • Create allelic series to study dosage effects

  • Generate tissue-specific knockouts using cell-type specific promoters

  • Perform multiplexed editing to target multiple iron transport genes simultaneously

  • Implement CRISPR interference (CRISPRi) or activation (CRISPRa) for reversible functional studies

These advanced gene editing approaches can complement traditional methods like QTL mapping to provide more precise insights into At1g21140 function.

What potential biotechnological applications could emerge from understanding At1g21140 function?

Understanding the function of At1g21140 could lead to various biotechnological applications with significant agricultural and environmental implications:

• Biofortification Strategies:

  • Engineering crops with enhanced iron content in edible tissues by modifying vacuolar iron transport

  • Developing varieties with improved iron bioavailability for addressing human nutritional deficiencies

  • Creating plants with optimized iron distribution for increased yield under limiting conditions

• Environmental Applications:

  • Engineering plants for phytoremediation of iron-contaminated soils

  • Developing bioindicators for iron availability in agricultural settings

  • Creating plants with enhanced tolerance to iron toxicity for cultivation in problematic soils

• Methodological Innovations:

  • Using At1g21140 as a vacuolar targeting system for other compounds of interest

  • Developing biosensors based on At1g21140 for monitoring iron levels

  • Creating selection markers for plant transformation based on iron homeostasis

• Agricultural Adaptations:

  • Breeding crops with enhanced performance under iron-limited conditions

  • Developing varieties with reduced fertilizer requirements

  • Engineering symbiotic relationships with enhanced iron exchange, based on understanding of related transporters like GmVTL1 in nodules

While these applications require thorough understanding of At1g21140 function and careful assessment of potential ecological impacts, they represent promising directions for translating basic research into practical solutions.

How might systems biology approaches integrate At1g21140 into broader iron homeostasis networks?

Systems biology approaches offer comprehensive frameworks for understanding At1g21140 function within the complex network of iron homeostasis. Based on methodologies mentioned in the search results and current systems biology practices:

• Multi-omics Integration:

  • Combine transcriptomics data with proteomics, metabolomics, and ionomics

  • Correlate At1g21140 expression with iron-responsive metabolic pathways

  • Map protein-protein interactions within iron transport networks

  • Integrate QTL data with molecular phenotypes for network modeling

• Mathematical Modeling Approaches:

  • Develop kinetic models of iron transport including At1g21140 activity

  • Create genome-scale metabolic models incorporating iron utilization pathways

  • Implement Boolean network models of iron signaling cascades

  • Construct hierarchical models connecting molecular mechanisms to whole-plant phenotypes

• Network Analysis Methods:

  • Identify hub genes and regulatory modules in iron homeostasis networks

  • Perform time-series analysis to capture dynamic responses to iron perturbations

  • Compare network topologies across different plant species

  • Identify emergent properties that arise from network interactions

• Experimental Validation Strategies:

  • Design targeted perturbation experiments to test model predictions

  • Implement synthetic biology approaches to reconstruct minimal networks

  • Develop high-throughput phenotyping systems for model validation

  • Use machine learning to identify patterns and make predictions based on integrated data

This systems-level understanding could reveal how At1g21140 coordinates with other transporters, such as the GmVTL family in soybean , to maintain iron homeostasis across different tissues and developmental stages.

What are the best practices for integrating multiple techniques in At1g21140 research?

Effective At1g21140 research requires integrating diverse techniques to build a comprehensive understanding of its function. Based on approaches described in the search results:

• Coordinated Experimental Design:

  • Begin with genetic resources like knockout mutants, overexpression lines, and STAIRS

  • Combine phenotypic characterization with molecular analyses

  • Integrate biochemical studies of the recombinant protein with in planta functional analyses

  • Design experiments that connect molecular mechanisms to whole-plant phenotypes

• Complementary Methodological Approaches:

  • Use recombinant protein studies to determine biochemical properties

  • Apply QTL mapping to identify genetic interactions and environmental influences

  • Employ transcriptomics to reveal regulatory networks

  • Implement protein localization and interaction studies to determine cellular context

• Data Integration Strategies:

  • Maintain consistent experimental conditions across different technique platforms

  • Develop standardized data management practices for cross-technique comparisons

  • Use computational approaches to integrate diverse data types

  • Implement statistical methods appropriate for complex, multi-technique datasets

• Collaborative Research Models:

  • Establish interdisciplinary collaborations spanning genetics, biochemistry, and physiology

  • Share standardized materials (e.g., recombinant proteins , genetic stocks )

  • Develop common phenotyping protocols for consistent data collection

  • Implement open data sharing to accelerate discovery

By integrating these approaches, researchers can develop a holistic understanding of At1g21140 function that spans from molecular mechanisms to ecological significance.

How should researchers document and report At1g21140 experimental protocols for reproducibility?

Ensuring reproducibility in At1g21140 research requires thorough documentation and reporting of experimental protocols. Based on best practices in the field and information from the search results:

• Detailed Material Documentation:

  • Provide complete protein characteristics including sequence, tag information, and storage conditions as shown in search result

  • Document the genetic background, generation, and confirmation of plant lines

  • Include source information for all reagents, kits, and equipment

  • Specify exact environmental conditions for plant growth

• Comprehensive Methodological Reporting:

  • Detail all steps in protocols with sufficient information for replication

  • For QTL analysis, specify all statistical approaches and software used

  • For recombinant protein work, include expression system, purification protocol, and quality control measures

  • Provide explicit descriptions of phenotyping methods with measurement parameters

• Data Processing and Analysis Transparency:

  • Share raw data through appropriate repositories

  • Provide all scripts and code used for data analysis

  • Document statistical approaches in detail, including decision criteria

  • Report both positive and negative results to avoid publication bias

• Standardized Reporting Formats:

  • Follow community standards for experimental reporting in plant science

  • Include comprehensive methods sections in publications

  • Consider publishing detailed protocols in dedicated journals

  • Deposit protocols in community repositories for wider access