Recombinant Pseudomonas syringae pv. tomato UPF0350 protein PSPTO_4227 (PSPTO_4227)

What is PSPTO_4227 and what is its genomic context?

PSPTO_4227 appears to be a UPF0350 family protein from Pseudomonas syringae pv. tomato strain DC3000 (ATCC BAA-871). Based on protein database information, it may function as a FAD assembly factor SdhE (sp|Q87XF1|SDHE_PSESM) . The gene is located within the Pseudomonas syringae genome and has been identified through whole-genome sequencing and annotation efforts.

Genomic context analysis reveals PSPTO_4227 is situated among genes involved in various metabolic pathways. Its positioning provides insights into potential functional relationships with neighboring genes that may participate in related biochemical processes within P. syringae.

What expression systems are recommended for recombinant PSPTO_4227 production?

For recombinant expression of PSPTO_4227, several expression systems can be employed based on research objectives:

• Bacterial systems: E. coli BL21(DE3) remains the primary choice for initial expression attempts due to its robust growth, high protein yields, and compatibility with various expression vectors. For PSPTO_4227, consider using pET-based vectors with N-terminal 6xHis and/or GST tags to facilitate purification.

• Alternative hosts: If proper folding is problematic in E. coli (indicated by inclusion body formation), consider Pseudomonas-based expression systems that provide a more native cellular environment.

When optimizing expression:

• Test multiple induction temperatures (16°C, 25°C, 37°C)

• Vary IPTG concentrations (0.1-1.0 mM)

• Explore different media formulations (LB, TB, auto-induction)

Based on similar bacterial proteins, optimal expression may occur at lower temperatures (16-20°C) with moderate inducer concentrations to prevent aggregation and maintain proper folding .

What purification strategies yield the highest purity PSPTO_4227?

The purification strategy should be tailored to the specific properties of PSPTO_4227:

• Initial capture: Immobilized metal affinity chromatography (IMAC) using Ni-NTA resins for His-tagged constructs. Buffer conditions should start with:

  • Buffer A: 50 mM Tris-HCl pH 8.0, 300 mM NaCl, 10 mM imidazole

  • Buffer B: 50 mM Tris-HCl pH 8.0, 300 mM NaCl, 500 mM imidazole

• Secondary purification: Size exclusion chromatography (SEC) using Superdex 75/200 columns is recommended to achieve >95% purity and remove aggregates.

• Additional considerations:

  • Include reducing agents (1-5 mM DTT or 1-2 mM β-mercaptoethanol) if cysteine residues are present

  • Test buffer pH ranges (pH 6.5-8.5) to optimize stability

  • Consider ion exchange chromatography as an intermediate step if contaminants persist

Based on similar bacterial proteins in the UPF0350 family, PSPTO_4227 likely requires careful optimization of salt concentrations to maintain solubility while preventing non-specific binding .

How can I determine the structural characteristics of PSPTO_4227?

Multiple complementary approaches should be employed to elucidate the structural features of PSPTO_4227:

• Computational prediction:

  • Secondary structure prediction using JPred, PSIPRED

  • Domain identification using InterPro, Pfam

  • Homology modeling if suitable templates exist (30%+ sequence identity)

• Experimental methods:

  • Circular dichroism (CD) spectroscopy to determine secondary structure composition

  • Limited proteolysis coupled with mass spectrometry to identify domain boundaries

  • Small-angle X-ray scattering (SAXS) for low-resolution solution structure

  • X-ray crystallography or cryo-EM for high-resolution structural determination

• NMR spectroscopy:

  • 1D/2D NMR to assess proper folding

  • Complete structure determination if protein size permits (<25 kDa)

When planning structural studies, consider that UPF0350 family proteins typically exhibit α/β fold characteristics. Based on FAD assembly factors like SdhE, PSPTO_4227 may have domains involved in FAD binding and protein-protein interactions that can be targeted in structural studies .

What techniques effectively characterize PSPTO_4227 protein-protein interactions?

To comprehensively characterize the interactome of PSPTO_4227, employ a multi-tiered approach:

• Initial screening methods:

  • Bacterial two-hybrid system or yeast two-hybrid adapted for bacterial proteins

  • Pull-down assays using tagged PSPTO_4227 followed by mass spectrometry

  • Co-immunoprecipitation from Pseudomonas syringae lysates

• Validation and quantification:

  • Surface plasmon resonance (SPR) or bio-layer interferometry (BLI) for binding kinetics

  • Isothermal titration calorimetry (ITC) for thermodynamic parameters

  • Microscale thermophoresis (MST) for interaction affinity in solution

• Structural characterization of complexes:

  • Hydrogen-deuterium exchange mass spectrometry (HDX-MS) to map interaction interfaces

  • Cross-linking mass spectrometry (XL-MS) to identify spatial proximity of residues

  • Co-crystallization or cryo-EM of PSPTO_4227 with binding partners

When analyzing protein interaction data, create network maps highlighting primary and secondary interaction partners. The data can be presented in interaction tables showing binding affinities (Kd values) and confidence scores, as exemplified by studies on similar bacterial proteins .

How does PSPTO_4227 function in Pseudomonas virulence and plant-pathogen interactions?

Understanding PSPTO_4227's role in virulence requires multiple complementary approaches:

• Gene knockout studies:

  • Create clean deletion mutants of PSPTO_4227 using allelic exchange

  • Assess virulence phenotypes in plant infection models

  • Complement with wild-type and point-mutated versions to confirm phenotypes

• Transcriptomic and proteomic analyses:

  • Compare expression profiles of wild-type vs. ΔPSPTO_4227 strains

  • Identify differentially expressed genes during infection

  • Analyze changes in secreted proteins and effectors

• Functional assays:

  • Measure bacterial growth curves in planta

  • Assess plant defense responses (ROS production, callose deposition)

  • Evaluate bacterial motility, biofilm formation, and type III secretion system function

If PSPTO_4227 functions as an FAD assembly factor similar to SdhE, investigate its impact on energy metabolism during infection and explore potential roles in oxidative stress resistance—a critical factor during plant infection .

What experimental design best evaluates PSPTO_4227 mutant phenotypes?

When designing experiments to evaluate PSPTO_4227 mutant phenotypes, implement a multiple-probe experimental design:

• Construct generation:

  • Create complete gene deletion (ΔPSPTO_4227)

  • Generate point mutations at predicted functional residues

  • Develop complementation constructs (wild-type and mutant versions)

• Phenotypic assessment protocol:

  • Establish baseline measurements through multiple pre-intervention probes

  • Implement temporal staggering of interventions to maintain experimental design fidelity

  • Include appropriate controls (wild-type, vector-only, unrelated gene deletion)

• Data collection parameters:

  • Growth characteristics (lag phase, doubling time, maximum density)

  • Virulence indicators (disease symptoms, bacterial titer in planta)

  • Molecular phenotypes (gene expression, protein levels, enzymatic activity)

The multiple-probe design allows for direct testing of target phenotypes and can provide estimates of phenotypic changes in response to environmental variables. Temporal staggering maintains experimental integrity while allowing the design to evolve with discovery .

What are the optimal conditions for analyzing PSPTO_4227 enzymatic activity?

If PSPTO_4227 functions as an FAD assembly factor (SdhE), the following enzymatic activity assay conditions should be considered:

• Buffer optimization:

  • Test pH range: 6.5-8.0 in 25 mM increments

  • Evaluate buffer systems: Tris-HCl, HEPES, Phosphate

  • Optimize salt concentration: 50-200 mM NaCl

• Assay components:

  • Substrate: FAD or FAD precursors

  • Target proteins: Succinate dehydrogenase components

  • Cofactors: Divalent cations (Mg²⁺, Mn²⁺)

  • Reducing agents: DTT or TCEP (0.5-2 mM)

• Detection methods:

  • Spectrophotometric monitoring of FAD incorporation (450 nm)

  • Fluorescence-based assays for FAD binding

  • Activity of reconstituted enzyme complexes (e.g., succinate dehydrogenase)

Create a systematic approach using the following data table format to document optimization experiments:

This methodical approach ensures reproducible activity measurements and helps identify optimal conditions for mechanistic studies .

How can I design effective site-directed mutagenesis experiments for PSPTO_4227?

To design informative site-directed mutagenesis experiments for PSPTO_4227:

• Target selection strategy:

  • Conserved residues identified through multiple sequence alignment of UPF0350 family proteins

  • Predicted functional sites from structural models or homology to characterized proteins

  • Charged/polar surface residues for potential protein-protein interaction interfaces

• Mutation design principles:

  • Conservative substitutions (e.g., D→E, K→R) to test charge importance

  • Alanine scanning to remove side chain functionality

  • Non-conservative substitutions to test specific hypotheses (e.g., D→K to reverse charge)

• Experimental validation approach:

  • Express and purify all mutants under identical conditions

  • Conduct systematic characterization (structure, stability, activity)

  • Compare in vitro and in vivo phenotypes

Document your mutational analysis using a structured table format:

This comprehensive approach allows for mechanistic insights while controlling for potential structural destabilization effects that could confound interpretation .

How do I interpret contradictory proteomics data for PSPTO_4227?

When faced with contradictory proteomics data for PSPTO_4227, implement the following systematic analysis approach:

• Data quality assessment:

  • Evaluate raw spectral quality (signal-to-noise ratio, peak resolution)

  • Check peptide identification confidence scores

  • Assess coverage of PSPTO_4227 sequence across replicates

• Methodological comparison:

  • Analyze differences in sample preparation protocols

  • Compare MS platforms and acquisition parameters

  • Evaluate different search algorithms and database versions

• Biological context integration:

  • Consider growth conditions and cellular states

  • Evaluate post-translational modification status

  • Examine protein complex formation

When analyzing proteomics data, organize results in a comprehensive table format similar to this excerpt from a Pseudomonas syringae proteomic study:

This structured approach allows for systematic evaluation of conflicting data points and identification of experimental variables that may account for discrepancies .

What statistical approaches are appropriate for analyzing PSPTO_4227 experimental data?

When analyzing experimental data related to PSPTO_4227, select appropriate statistical methods based on experimental design and data characteristics:

• For comparing expression levels or activity:

  • t-test (paired or unpaired) for two-condition comparisons

  • ANOVA with post-hoc tests (Tukey, Dunnett) for multiple conditions

  • Non-parametric alternatives (Mann-Whitney, Kruskal-Wallis) for non-normally distributed data

• For correlation analyses:

  • Pearson correlation for linear relationships between variables

  • Spearman rank correlation for monotonic but non-linear relationships

  • Multiple regression for complex relationships with multiple variables

• For high-throughput data:

  • Apply appropriate multiple testing corrections (Bonferroni, FDR)

  • Consider dimensionality reduction techniques (PCA, t-SNE)

  • Implement specialized analysis pipelines for proteomics/transcriptomics

When preparing your statistical analysis:

• Define significance thresholds a priori (typically p < 0.05)

• Report effect sizes alongside p-values

• Include power calculations to justify sample sizes

• Present data graphically with appropriate error bars

For frequencies and descriptive statistics, implement approaches that account for missing data points, calculate standard error of the mean, and evaluate distribution characteristics including variance, skewness, and kurtosis4.

How can I troubleshoot low yields of recombinant PSPTO_4227?

When encountering low yields of recombinant PSPTO_4227, systematically address potential issues:

• Expression optimization:

  • Modify codon usage for E. coli preference

  • Test multiple expression strains (BL21, Rosetta, Arctic Express)

  • Reduce expression temperature (16-20°C) and inducer concentration

  • Try auto-induction media for gradual protein expression

• Solubility enhancement:

  • Add solubility tags (MBP, SUMO, TrxA) to the protein construct

  • Include stabilizing additives in lysis buffer (10% glycerol, 0.1% Triton X-100)

  • Test different cell disruption methods (sonication vs. French press)

  • Optimize lysis buffer components (salt, pH, reducing agents)

• Purification refinement:

  • Adjust imidazole concentrations in binding/wash buffers

  • Implement step gradients for elution

  • Include protease inhibitors to prevent degradation

  • Minimize processing time to reduce protein loss

Document your optimization efforts in a structured format:

This methodical troubleshooting approach allows for cumulative improvements in protein yield and can result in significantly higher quantities of functional PSPTO_4227 .

What emerging technologies could advance PSPTO_4227 functional characterization?

Several cutting-edge technologies hold promise for deeper functional characterization of PSPTO_4227:

• Structural biology innovations:

  • AlphaFold2 and RoseTTAFold for accurate structural prediction

  • Cryo-EM advances for membrane protein and complex structures

  • Integrative structural biology combining multiple data sources (SAXS, HDX-MS, XL-MS)

• Systems biology approaches:

  • CRISPRi screens in Pseudomonas for genetic interaction mapping

  • Proximity labeling (TurboID, APEX) to identify interacting partners in vivo

  • Metabolomics to detect changes in FAD-dependent pathways

• Single-cell technologies:

  • Single-cell RNA-seq during infection to capture heterogeneity

  • Time-lapse microscopy with fluorescent reporters

  • Microfluidics for controlled microenvironments

These technologies could reveal PSPTO_4227's function in the context of complex bacterial responses during plant infection and identify potential interplay with host defense mechanisms. The integration of computational and experimental approaches will be particularly powerful for generating testable hypotheses about this UPF0350 family protein .

How might PSPTO_4227 research contribute to broader understanding of plant-pathogen interactions?

Research on PSPTO_4227 has significant potential to advance our understanding of plant-pathogen interactions through multiple avenues:

• Metabolic adaptation mechanisms:

  • If PSPTO_4227 functions as an FAD assembly factor, it may reveal how pathogens adapt their energy metabolism during infection

  • Understanding pathogen metabolic requirements could identify new vulnerability points

• Evolutionary insights:

  • Comparative genomics across Pseudomonas species could reveal adaptation patterns

  • Analysis of selection pressure on PSPTO_4227 may indicate its importance in host specificity

• Host-pathogen signaling:

  • PSPTO_4227 may indirectly influence effector secretion or sensing mechanisms

  • Its activity might mediate responses to plant defense-generated oxidative stress

This research could contribute to development of novel disease management strategies by:

• Identifying new targets for antimicrobial development

• Informing breeding programs for plant resistance

• Enabling predictive models of pathogen adaptation

The broader impacts extend beyond Pseudomonas syringae to inform our understanding of fundamental mechanisms in plant-microbe interactions and bacterial adaptation to diverse ecological niches .

What interdisciplinary approaches could enhance PSPTO_4227 research outcomes?

Maximizing research impact for PSPTO_4227 requires integration across disciplines:

• Computational and experimental integration:

  • Machine learning models trained on experimental data to predict protein function

  • Network analysis connecting PSPTO_4227 to virulence pathways

  • In silico design of experiments to test specific hypotheses

• Multi-organism systems approach:

  • Plant-Pseudomonas co-culture systems with live-cell imaging

  • Synthetic biology tools to modulate PSPTO_4227 expression

  • Incorporation of microbiome context in experimental design

• Translational connections:

  • Agricultural biotechnology applications for disease resistance

  • Comparative analysis with human bacterial pathogens using similar mechanisms

  • Ecological studies examining environmental adaptations

The People Also Ask framework can guide interdisciplinary research by identifying knowledge gaps and prioritizing questions most relevant to diverse stakeholders . A well-structured experimental design that embeds probes within baseline testing and following mastery of trained targets can effectively capture the emerging knowledge about PSPTO_4227 while maintaining scientific rigor .