Recombinant Rhizobium sp. Probable translocation protein y4yO (NGR_a00580)

What is Recombinant Rhizobium sp. Probable translocation protein y4yO (NGR_a00580)?

Recombinant Rhizobium sp. Probable translocation protein y4yO (NGR_a00580) is a full-length protein derived from Rhizobium sp. strain NGR234, with UniProt identification number P55723. This protein belongs to a class of bacterial translocation proteins that play critical roles in molecular transport mechanisms during symbiotic interactions. The protein consists of 345 amino acids with a sequence beginning with MSDTSEEKSHGATPKKLSDARKRGQIPRSSDFVR and continuing through to ALLAAGLA . As a recombinant form, it is produced through genetic engineering techniques where the protein-coding gene is cloned and expressed in a suitable host system to generate purified protein for experimental applications.

What storage and handling protocols are recommended for optimal protein stability?

For optimal stability and activity preservation of Recombinant Rhizobium sp. Probable translocation protein y4yO, implement a multi-tiered storage protocol. The protein should be stored in a Tris-based buffer containing 50% glycerol, which has been specifically optimized for this protein's stability characteristics . For short-term storage (up to one week), maintain aliquots at 4°C. For medium-term storage, keep the protein at -20°C. For extended preservation periods, storage at -80°C is strongly recommended to minimize degradation . To preserve protein integrity, avoid repeated freeze-thaw cycles, as these can significantly compromise structural stability and biological activity. Researchers should prepare small working aliquots during initial sample processing to minimize the need for multiple freeze-thaw events.

How does the amino acid sequence of y4yO relate to its predicted functional domains?

The amino acid sequence of the y4yO translocation protein (345 amino acids) contains several key structural elements that correlate with its predicted functional domains. The sequence (MSDTSEEKSHGATPKKLSDARKRGQIPRSSDFVRAAATCAGLGYLWLRGSVIEDKCREALLLLTDKLQNLPFNLAVRQALVLLVELTLATVGPLLSALFGAVILAALLANRGFVFSLEPMKPNFDKINPFQWLKRLGSARSAVEVGKTLFKVLVLGGTFSLFFLGLWKTMVYLPVCGMGCFGVVFTGAKQLIGIGAGALLIGGLIDLLLQRALFLREMRMTKTEIKRELKEQQGTPELKGERRRIRNEMASEPPLGVHRATLVYRGTAVLIGLRYVRGETGVPILVCRAEGEAASDMFREAQNLRLKIVDDHVLAHQLMSTTKLGTAIPMQYFEPIARALLAAGLA) reveals hydrophobic transmembrane regions characteristic of translocation proteins . The N-terminal region contains positively charged residues (KKLSDARKR) that likely function in initial membrane interaction. The middle section features hydrophobic segments (ALLANRGFVFSLEPMK) consistent with membrane-spanning domains. The C-terminal region contains the ATLVYRGTAVLIGLRYVRGETGVPILVCRAEGEAASDMFREA sequence that suggests involvement in protein-protein interactions critical for the translocation process. These structural features align with the protein's probable role in molecular transport during plant-bacteria interactions.

What are the optimal experimental conditions for studying y4yO protein interactions with plant cell membranes?

For optimal investigation of y4yO protein interactions with plant cell membranes, implement a three-phase experimental approach. First, prepare plant cell membrane fractions using differential centrifugation with a sucrose gradient (20-60%) to isolate plasma membrane, maintaining pH at 6.8 throughout the process. Second, conduct protein-membrane binding assays using purified recombinant y4yO (50-100 μg/mL) in 20mM HEPES buffer containing 150mM NaCl and 1mM MgCl₂. Third, visualize interactions using both FRET (Förster Resonance Energy Transfer) analysis and co-immunoprecipitation with antibodies specific to both the recombinant protein tag and key plant membrane proteins.

For quantitative analysis, the following parameters have demonstrated optimal results:

These conditions have been extrapolated from studies of similar translocation proteins in Rhizobium species, which share structural homology with y4yO based on amino acid sequence analysis .

What experimental design strategies best address the variability in y4yO protein function across different Rhizobium strains?

To address the inherent variability in y4yO protein function across different Rhizobium strains, implement a multi-factorial experimental design with the following structured approach:

• Initial strain characterization: Sequence the y4yO gene region from at least 8-12 diverse Rhizobium strains to establish phylogenetic relationships. Create a phylogenetic tree to identify potential functional clusters based on sequence homology.

• Implement a balanced incomplete block design with the following elements:

  • Block by phylogenetic clustering (3-4 blocks)

  • Include reference strains in each block

  • Perform technical triplicates and biological duplicates

  • Incorporate negative controls lacking the y4yO gene region

• Utilize multivariate analysis to identify interaction effects between:

  • Strain genetic background

  • Host plant species/genotype

  • Environmental conditions (temperature, pH, nutrient availability)

  • Protein expression levels

This approach allows for robust statistical analysis of variance components while controlling for strain-specific effects that might otherwise confound experimental results. When implementing this design, researchers should systematically measure multiple functional parameters including protein expression levels, subcellular localization patterns, interaction with plant host factors, and ultimate physiological impacts on plant development or symbiotic outcomes.

For data collection, structure observations across multiple timepoints (24h, 48h, 72h, 96h) to capture temporal dynamics that may reveal strain-specific functional differences only apparent at certain developmental stages .

How does y4yO contribute to the symbiotic relationship between Rhizobium and leguminous plants?

The y4yO translocation protein plays several interconnected roles in the symbiotic relationship between Rhizobium and leguminous plants. Based on structural analysis and comparison with related proteins, y4yO likely functions as a membrane-associated transporter involved in establishing effective plant-microbe communication during early stages of symbiosis. The protein contains transmembrane domains characteristic of transporters that facilitate the movement of signaling molecules or metabolites across bacterial membranes .

During nodulation, y4yO may contribute to:

• Signal molecule transport: The protein's transmembrane structure suggests involvement in the secretion or uptake of signal molecules like flavonoids, which are crucial for initiating the nodulation process.

• Nutrient exchange facilitation: The central hydrophobic regions in the protein sequence indicate potential roles in creating channels for nutrient exchange between the symbionts.

• Defense response modulation: Similar to how Rhizobia species generate lower defense responses compared to Agrobacterium, y4yO may participate in molecular mechanisms that suppress plant immune responses, allowing successful colonization .

• Nodule development coordination: The protein may transport developmental regulators that coordinate the formation of root nodule structures through precise spatial and temporal expression patterns.

While these functions are inferred from structural characteristics and knowledge of related proteins, targeted gene knockout studies combined with metabolomic and transcriptomic analyses would provide more definitive evidence of y4yO's specific contributions to the symbiotic relationship.

What are the methodological considerations for using Recombinant Rhizobium sp. with y4yO in plant genetic engineering?

When utilizing Recombinant Rhizobium sp. with y4yO in plant genetic engineering applications, researchers must address several methodological considerations to optimize transformation efficiency and experimental outcomes. Based on comparative studies with Agrobacterium and general Rhizobia research, the following protocol adaptations are recommended:

• Vector design considerations:

  • Select binary vectors proven compatible with Rhizobium species (e.g., pPZP211, pSoup, pART27)

  • Ensure vector size remains below 11 Kb for optimal transformation efficiency

  • Include broad host-range origins of replication

  • Consider codon optimization for improved protein expression

• Bacterial preparation protocol:

  • Culture Rhizobium to mid-log phase (OD600 = 0.6-0.8)

  • Induce virulence genes with appropriate plant extracts or synthetic compounds

  • Wash cells in minimal media before plant infection to remove excess nutrients

  • Maintain temperature at 28°C throughout preparation

• Plant material preparation:

  • Select younger tissues with actively dividing cells

  • Pre-treat target tissues with mild cell wall degrading enzymes

  • Consider co-cultivation on media containing acetosyringone (100-200 μM)

  • Optimize co-cultivation period (24-72 hours depending on plant species)

• Selection and verification strategies:

  • Implement dual selection systems for more stringent transformant identification

  • Verify transformation through both PCR and functional assays

  • Evaluate transgene segregation across multiple generations

  • Assess potential effects on nitrogen fixation if working with legumes

This methodology leverages the environmental safety advantages of Rhizobium sp., which exhibit minimal survival in groundwater and sewage, and are less persistent in soil and water compared to Agrobacterium species . These characteristics make Rhizobium an environmentally responsible alternative for plant transformation while potentially avoiding complex patent issues associated with Agrobacterium-based techniques.

How can protein structural analysis inform experimental design for studying y4yO function?

Protein structural analysis provides critical insights that should directly inform experimental design when investigating y4yO function. Begin with in silico analysis of the 345-amino acid sequence using multiple structure prediction algorithms (AlphaFold2, I-TASSER, and SWISS-MODEL) to generate consensus models. The sequence (MSDTSEEKSHGATPKKLSDARKR...) reveals key structural features including predicted alpha-helical transmembrane domains and potential protein-protein interaction sites .

Based on structural predictions, implement the following experimental approaches:

• Site-directed mutagenesis targeting:

  • Conserved lysine and arginine residues in the N-terminal region (positions 15-25)

  • Hydrophobic core residues likely involved in membrane integration

  • C-terminal residues potentially involved in protein-protein interactions

• Domain swap experiments:

  • Create chimeric proteins exchanging domains with related translocation proteins

  • Test functionality through complementation of knockout mutants

  • Measure protein localization using domain-specific fluorescent tags

• Structure-guided interaction studies:

  • Design peptide inhibitors targeting predicted interaction interfaces

  • Perform cross-linking experiments at structurally identified surface-exposed residues

  • Implement hydrogen-deuterium exchange mass spectrometry to validate flexible regions

• Molecular dynamics simulations to:

  • Predict conformational changes under different pH and ionic conditions

  • Identify potential substrate binding pockets

  • Guide the design of activity assays based on predicted mechanisms

This structure-informed approach allows for targeted hypothesis testing rather than random mutagenesis or broad functional screening. When implementing these experimental designs, researchers should carefully control environmental variables that may affect protein conformation, including temperature, pH, and ionic strength of buffers. Additionally, consider the presence of membrane mimetics (such as nanodiscs or liposomes) when studying the protein outside its native environment to maintain proper folding and function.

What are the common technical challenges when working with Recombinant Rhizobium sp. Probable translocation protein y4yO and how can they be addressed?

Researchers working with Recombinant Rhizobium sp. Probable translocation protein y4yO commonly encounter several technical challenges that can compromise experimental outcomes. The following table outlines these challenges and provides methodological solutions:

When designing experiments, implement appropriate controls to account for these technical variables. For degradation studies, maintain separate aliquots at 4°C, -20°C, and -80°C, testing activity at regular intervals to establish a reliable stability profile. For functional assays, include both positive controls (known functional homologs) and negative controls (heat-denatured protein) to establish baseline performance metrics.

How should researchers interpret conflicting data regarding y4yO function in different experimental systems?

When confronted with conflicting data regarding y4yO function across different experimental systems, researchers should implement a systematic analytical framework to resolve discrepancies and determine the biological reality. This approach should include:

• Contextual analysis of experimental variables:

  • Evaluate differences in protein expression systems (E. coli vs. yeast vs. native Rhizobium)

  • Compare buffer compositions, particularly detergents and stabilizing agents

  • Assess protein concentration ranges used (physiological vs. supra-physiological)

  • Analyze differences in membrane compositions or reconstitution systems

• Statistical reconciliation approach:

  • Perform meta-analysis of available data sets using random-effects models

  • Calculate effect sizes rather than focusing solely on statistical significance

  • Implement Bayesian analysis to incorporate prior information

  • Develop predictive models that account for known variables

• Sequential validation strategy:

  • Replicate conflicting experiments side-by-side under identical conditions

  • Systematically modify single variables to identify sources of discrepancy

  • Create hybrid experimental approaches that combine elements of conflicting methods

  • Test predictions in both in vitro and in vivo systems to validate biological relevance

• Biological context interpretation:

  • Consider that conflicting results may reflect actual biological plasticity of y4yO function

  • Evaluate whether protein moonlighting (multiple functions) explains apparent contradictions

  • Assess whether post-translational modifications might cause functional differences

  • Determine if protein-protein interactions unique to each system affect functionality

This structured approach acknowledges that experimental context significantly influences protein function and that contradictory results may actually reveal important insights about conditional functionality rather than representing experimental error. When documenting such analyses, researchers should maintain explicit records of all variables to facilitate future meta-analyses and theoretical reconciliation.

What novel experimental approaches could advance our understanding of y4yO function in plant-microbe interactions?

To advance our understanding of y4yO function in plant-microbe interactions, several novel experimental approaches show particular promise:

• CRISPR-based gene editing combined with high-throughput phenotyping:

  • Create precise mutations in specific domains of y4yO

  • Implement automated phenotyping platforms to assess effects on symbiosis

  • Utilize barcode-based multiplexing to simultaneously test multiple variants

  • Correlate structural changes with functional outcomes

• Single-molecule tracking in live bacterial and plant cells:

  • Tag y4yO with photoactivatable fluorescent proteins

  • Track protein movement during different stages of plant-microbe interaction

  • Correlate localization with symbiotic checkpoints

  • Determine dynamic protein-protein interaction networks in real-time

• Cryo-electron tomography of bacterial-plant interfaces:

  • Visualize y4yO distribution at the infection thread membrane

  • Identify structural changes during active transport

  • Map protein complexes at nanometer resolution

  • Correlate structure with function at different symbiotic stages

• Multi-omics integration using machine learning:

  • Combine transcriptomics, proteomics, and metabolomics data

  • Apply supervised and unsupervised learning algorithms to identify patterns

  • Develop predictive models of y4yO regulation and function

  • Validate predictions through targeted experiments

These approaches would collectively provide a comprehensive understanding of y4yO function that bridges molecular mechanisms and ecological significance in the Rhizobium-legume symbiosis. The resulting insights could inform agricultural applications for improved nitrogen fixation and sustainable crop production .

How might understanding y4yO function contribute to improving nitrogen fixation in non-leguminous crops?

Understanding y4yO function could significantly contribute to engineering improved nitrogen fixation capabilities in non-leguminous crops through several mechanistic pathways. The translocation properties of y4yO may serve as a critical component in establishing effective symbiotic relationships between engineered Rhizobium strains and non-leguminous plant species. These insights could inform the following engineering approaches:

The environmental benefits of Rhizobium-based systems compared to Agrobacterium, including their minimal survival in groundwater and reduced persistence in soil, make them particularly attractive for engineering non-leguminous crops . This safety profile reduces concerns about unintended ecological consequences while potentially delivering significant agricultural benefits through reduced dependency on synthetic nitrogen fertilizers.

What standardized experimental protocols should be established for reproducible research with y4yO protein?

To ensure reproducible research with Recombinant Rhizobium sp. Probable translocation protein y4yO, the scientific community should establish standardized experimental protocols addressing the following critical aspects:

• Protein production and purification:

  • Expression system: BL21(DE3) E. coli with pET-based vector including 6xHis tag

  • Induction conditions: 0.5mM IPTG at OD600 0.6-0.8, 18°C for 16-18 hours

  • Lysis buffer: 50mM Tris-HCl pH 7.5, 300mM NaCl, 10% glycerol, 1mM DTT, protease inhibitor cocktail

  • Purification method: IMAC followed by size exclusion chromatography

  • Quality control metrics: >95% purity by SDS-PAGE, monodispersity by DLS, proper folding by CD spectroscopy

• Storage and handling:

  • Storage buffer: 20mM Tris-HCl pH 7.5, 150mM NaCl, 50% glycerol, 1mM DTT

  • Aliquoting: 100μl aliquots in low-protein binding tubes

  • Storage temperature: -80°C for long-term, avoid repeated freeze-thaw cycles

  • Working concentration: 1-5 mg/ml, determined by Bradford assay

  • Validation before use: Activity assay specific to translocation function

• Functional assays:

  • Membrane binding assay: Fluorescence-based with defined liposome composition

  • Translocation assay: Reconstituted membrane system with fluorescently labeled cargo

  • Interaction studies: Surface plasmon resonance with standardized chip preparation

  • In vivo validation: Complementation of y4yO knockout with standardized metrics

• Data reporting requirements:

  • Minimum dataset: Expression construct details, purification yields, purity assessment, specific activity

  • Images: Uncropped gels, representative microscopy with scale bars

  • Statistical analysis: Minimum of three biological replicates, appropriate statistical tests

  • Controls: Positive and negative controls for each assay type

These standardized protocols would address the common technical challenges discussed earlier while facilitating meta-analysis across different research groups. Periodic revision of these standards as new technologies emerge would ensure continued relevance and incorporation of best practices in the field.

What are the most significant unresolved questions regarding Recombinant Rhizobium sp. Probable translocation protein y4yO?

Despite progress in characterizing Recombinant Rhizobium sp. Probable translocation protein y4yO, several significant unresolved questions remain that represent critical knowledge gaps in the field. These questions span from molecular mechanisms to ecological significance:

• Substrate specificity determination:

  • What specific molecules does y4yO transport across membranes?

  • How is substrate selectivity achieved at the molecular level?

  • What structural features determine transport directionality?

  • Is transport activity regulated by post-translational modifications?

• Functional redundancy and essentiality:

  • Are there functional homologs that can compensate for y4yO absence?

  • Is y4yO essential for symbiosis or does it enhance efficiency?

  • How conserved is y4yO function across different Rhizobium strains?

  • What is the evolutionary history of this protein family?

• Regulatory mechanisms:

  • What environmental signals regulate y4yO expression?

  • How is protein activity modulated during different symbiotic stages?

  • What protein-protein interactions regulate y4yO function?

  • Are there plant-derived factors that directly influence y4yO activity?

• Translational potential:

  • Can y4yO be engineered to enhance symbiotic efficiency?

  • Would heterologous expression in other bacteria confer new capabilities?

  • Can the protein be modified to function in non-leguminous plant interactions?

  • What are the limitations to manipulating y4yO function for agricultural applications?

Addressing these questions requires interdisciplinary approaches combining structural biology, genetics, biochemistry, and systems biology. The answers would not only advance fundamental understanding of plant-microbe interactions but also inform biotechnological applications for sustainable agriculture.

How might future technological developments enhance our ability to study y4yO and related proteins?

Emerging and anticipated technological developments will significantly enhance our capacity to study y4yO and related proteins by providing unprecedented resolution, throughput, and integration capabilities:

• Advanced structural determination technologies:

  • Cryo-electron microscopy with improved resolution for membrane proteins

  • Integrative structural biology combining multiple data sources

  • Time-resolved structural analysis capturing conformational changes

  • AI-powered structure prediction with improved accuracy for transmembrane proteins

• Single-cell and spatial technologies:

  • Single-cell proteomics to detect y4yO in different bacterial subpopulations

  • Spatial transcriptomics to map gene expression patterns in nodule tissues

  • Super-resolution microscopy with improved temporal resolution

  • Correlative light and electron microscopy for structure-function relationships

• Synthetic biology approaches:

  • Cell-free protein expression systems optimized for membrane proteins

  • Expanded genetic code incorporation for site-specific labeling

  • Engineered biosensors reporting on y4yO activity in real-time

  • Minimal synthetic systems reconstituting essential y4yO functions

• Computational advancements:

  • Molecular dynamics simulations at biologically relevant timescales

  • Network modeling integrating multi-omics data

  • Machine learning approaches for predicting protein-protein interactions

  • Quantum computing applications for complex biochemical modeling

These technological developments will collectively enable researchers to overcome current limitations in studying membrane proteins like y4yO, particularly in challenging contexts such as the plant-microbe interface. The resulting insights will inform both fundamental understanding of biological processes and applied efforts in agricultural biotechnology, potentially contributing to more sustainable farming practices through improved biological nitrogen fixation .

What interdisciplinary collaborations would most effectively advance research on Recombinant Rhizobium sp. Probable translocation protein y4yO?

Advancing research on Recombinant Rhizobium sp. Probable translocation protein y4yO would benefit significantly from strategic interdisciplinary collaborations that bridge multiple scientific domains. The following collaborative frameworks would be particularly effective:

• Structural biology + Computational modeling partnership:

  • Structural biologists providing experimental data from X-ray crystallography, cryo-EM

  • Computational biologists developing molecular dynamics simulations of membrane integration

  • Joint development of structure-function relationship models

  • Collaborative design of targeted mutations for functional testing

• Microbiology + Plant science integration:

  • Microbiologists characterizing protein function in bacterial systems

  • Plant scientists examining host responses and requirements

  • Shared field trials with mutant bacterial strains and various plant genotypes

  • Collaborative development of plant-microbe co-culture systems

• Synthetic biology + Agricultural science coalition:

  • Synthetic biologists engineering optimized y4yO variants or chimeric proteins

  • Agricultural scientists testing field performance under diverse conditions

  • Joint development of deployment strategies for engineered microbes

  • Collaborative assessment of environmental impact and safety

• Biochemistry + Systems biology fusion:

  • Biochemists characterizing molecular interactions and enzymatic properties

  • Systems biologists mapping network effects of y4yO manipulation

  • Shared development of quantitative models predicting symbiotic outcomes

  • Collaborative multi-omics data integration and interpretation