Recombinant Pseudomonas syringae pv. tomato UPF0345 protein PSPTO_2022 (PSPTO_2022)

What is the function of PSPTO_2022 in Pseudomonas syringae pv. tomato?

PSPTO_2022 belongs to the UPF0345 protein family, which remains functionally uncharacterized but appears to be involved in bacterial virulence processes. Current evidence suggests it may participate in plant-pathogen interactions, potentially contributing to bacterial entry into the plant apoplast similar to other Pseudomonas syringae proteins. Research has demonstrated that several proteins in Pseudomonas syringae pv. tomato play critical roles in virulence by facilitating chemotaxis toward plant-derived compounds to locate entry points into the plant tissue .

To investigate its function:

• Conduct gene knockout studies using homologous recombination

• Perform complementation assays to verify phenotypes

• Utilize bacterial two-hybrid systems to identify protein interaction partners

• Compare virulence between wild-type and mutant strains through infiltration and spray inoculation methods

What expression systems are most suitable for recombinant PSPTO_2022 production?

The optimal expression system depends on experimental requirements. For structural studies requiring high protein yield, bacterial expression systems (E. coli BL21(DE3) or similar strains) are generally preferred. For functional studies, yeast or insect cell systems may better preserve protein folding and post-translational modifications.

When expressing PSPTO_2022 in plant systems, researchers should carefully consider promoter selection, as certain promoters like the 35S promoter can cause stability issues in Agrobacterium-based transformation systems. Evidence from similar recombinant protein expression attempts shows that the 35S promoter may be susceptible to transposon insertion when passing through Agrobacterium tumefaciens LBA4404 .

Consider this comparative expression system data:

How can I verify the functional activity of purified recombinant PSPTO_2022?

Functional verification of PSPTO_2022 requires multiple approaches:

• Biochemical assays: Develop assays based on predicted function, possibly related to chemotaxis or virulence

• Plant infection assays: Compare the ability of wild-type and PSPTO_2022-deficient bacteria to infect tomato plants

• Complementation studies: Rescue phenotypes in knockout mutants with the purified protein

• Structure-function analysis: Use site-directed mutagenesis to identify critical residues

What are the challenges in resolving the crystal structure of PSPTO_2022 and how can they be addressed?

Obtaining crystal structures of uncharacterized proteins like PSPTO_2022 presents several challenges:

• Protein solubility and stability issues

• Difficulty in obtaining homogeneous protein samples

• Challenges in crystal formation and quality

• Phase determination problems without homologous structures

Methodological approaches to address these challenges include:

Protein engineering strategies:

• Generate truncated constructs based on bioinformatic domain predictions

• Create fusion proteins with highly soluble partners (MBP, SUMO, Thioredoxin)

• Introduce surface entropy reduction mutations to facilitate crystal packing

• Perform limited proteolysis to identify stable domains

Crystallization optimization:

• Implement high-throughput screening of crystallization conditions

• Use seeding techniques to improve crystal quality

• Explore additive screens to enhance crystal formation

• Consider alternative crystallization methods (lipidic cubic phase for membrane-associated regions)

For proteins resistant to crystallization, alternative structural biology approaches such as cryo-EM, NMR spectroscopy (for smaller domains), or integrative structural modeling can be employed.

How do environmental conditions affect PSPTO_2022 expression and function during tomato infection?

Environmental factors significantly impact bacterial virulence gene expression. For PSPTO_2022, consider investigating:

• Temperature effects: Compare expression and function at different temperatures (15-28°C)

• pH responsiveness: Analyze expression changes across relevant apoplastic pH ranges (4.5-6.5)

• Nutrient availability: Examine the impact of different carbon/nitrogen sources

• Plant defense molecule presence: Test how plant-derived compounds affect expression

Based on similar Pseudomonas research, specific plant-derived amino acids like GABA and L-Pro can serve as important signals that regulate bacterial gene expression. These compounds are known to increase significantly in tomato plants upon pathogen infection and are involved in regulating plant defense responses . To study this relationship:

• Quantify PSPTO_2022 expression under different GABA/L-Pro concentrations

• Measure amino acid levels in infected versus uninfected plant tissues

• Correlate PSPTO_2022 expression with symptom development under various conditions

This data table illustrates how environmental factors might affect PSPTO_2022 expression:

What are the contradictions in the literature regarding PSPTO_2022 function and how can they be resolved?

As with many uncharacterized proteins, conflicting hypotheses about PSPTO_2022 function may exist in the literature. These contradictions typically arise from:

• Different experimental systems (in vitro vs. in planta)

• Varied bacterial strains or plant cultivars used across studies

• Differing environmental conditions during experiments

• Limitations in experimental approaches

To resolve these contradictions:

Methodological approach:

• Perform comprehensive literature meta-analysis, categorizing studies by experimental conditions

• Design experiments that directly address contradictory findings using standardized conditions

• Develop reporter systems to monitor PSPTO_2022 expression in real-time during infection

• Use multiple complementary approaches to verify function (transcriptomics, proteomics, metabolomics)

Consider developing a standardized infection model that controls for variables known to affect Pseudomonas syringae pv. tomato infection, such as entry method (spray vs. infiltration), inoculum concentration, plant age, and environmental conditions .

What is the optimal protocol for expressing recombinant PSPTO_2022 in plant expression systems?

Based on experience with similar recombinant proteins, the following methodology is recommended for plant-based expression of PSPTO_2022:

Expression vector design:

• Select an appropriate plant promoter that remains stable in Agrobacterium (consider the PMA4 promoter instead of the 35S promoter which can be susceptible to transposon insertion)

• Include an effective signal peptide (such as Medicago sativa protein disulfide isomerase signal peptide) for protein secretion

• Add a purification tag (6xHis) for downstream purification

• Consider including genetic insulators (such as RB7 SAR) to enhance expression stability

Transformation methodology:

• For Agrobacterium-mediated transformation, use GV3101 strain rather than LBA4404 to avoid transposon insertion issues

• Alternatively, consider direct transformation methods like biolistics that bypass Agrobacterium-related complications

• Verify plasmid integrity in Agrobacterium before plant transformation through restriction digestion analysis

Expression optimization:

• Screen multiple independent transgenic lines for expression levels

• Test different plant tissues and developmental stages for optimal expression

• Consider using plant species with reduced proteolytic activity or co-express protease inhibitors

As demonstrated in similar expression studies, transposon insertion can significantly affect recombinant protein expression in plant systems when using certain promoters and Agrobacterium strains . Careful monitoring of vector integrity at each transformation step is essential.

How can I troubleshoot low yield or degradation issues when purifying PSPTO_2022?

Protein purification troubleshooting requires systematic analysis of each step:

Expression phase issues:

• Verify mRNA expression through RT-PCR

• Check for premature transcription termination

• Evaluate codon optimization for the expression system

• Test different induction conditions or expression times

Solubility challenges:

• Implement solubility screens with various buffers and additives

• Test fusion partners known to enhance solubility (MBP, SUMO, Thioredoxin)

• Consider co-expression with chaperones

• Explore refolding protocols from inclusion bodies if necessary

Purification process optimization:

• Test multiple purification strategies (IMAC, ion exchange, size exclusion)

• Include protease inhibitors throughout the purification process

• Maintain cold temperatures during all purification steps

• Implement gentle elution conditions to preserve protein structure

Stability enhancement:

• Screen buffer conditions using differential scanning fluorimetry

• Identify stabilizing additives (glycerol, specific salts, reducing agents)

• Determine optimal pH and ionic strength conditions

• Consider storage in small aliquots at -80°C with cryoprotectants

When expressing in plant systems, specific attention should be paid to proteolytic degradation, as plant proteases can significantly reduce recombinant protein yields .

What are the most effective approaches for studying PSPTO_2022 interactions with plant defense compounds?

To study how PSPTO_2022 interacts with plant defense compounds, implement these methodological approaches:

In vitro interaction studies:

• Surface plasmon resonance (SPR) to determine binding kinetics with purified plant molecules

• Isothermal titration calorimetry (ITC) for thermodynamic binding parameters

• Microscale thermophoresis for detecting interactions in complex solutions

• Fluorescence-based binding assays for high-throughput screening

In vivo monitoring approaches:

• Develop fluorescently tagged PSPTO_2022 constructs to visualize localization during infection

• Create transcriptional/translational reporters to monitor expression in response to plant compounds

• Use split-reporter systems to detect protein-protein interactions during infection

• Implement metabolic labeling to track protein modifications in response to plant signals

Plant defense compound analysis:

• Quantify GABA and L-Pro levels in plant tissues before and after infection

• Measure changes in amino acid profiles during different infection stages

• Correlate defense compound concentrations with PSPTO_2022 expression levels

Research has shown that compounds like GABA and L-Pro significantly increase in tomato plants upon pathogen infection and are involved in regulating plant defense responses . The perception of these compounds by bacterial chemoreceptors can drive bacterial entry into the plant apoplast and ensure efficient infection, suggesting a potential area for investigation with PSPTO_2022.

How should RNA-seq data from PSPTO_2022 knockout studies be properly analyzed?

RNA-seq analysis of PSPTO_2022 knockout mutants requires careful experimental design and rigorous bioinformatic analysis:

Experimental design considerations:

• Include biological replicates (minimum 3-4 per condition)

• Compare multiple growth conditions (minimal media, plant extract supplementation, in planta)

• Include appropriate controls (wild-type, complemented mutant, unrelated gene knockout)

• Sample at multiple time points to capture temporal expression dynamics

Bioinformatic analysis workflow:

• Quality control and preprocessing (adapter trimming, quality filtering)

• Read alignment to reference genome (consider using HISAT2 or STAR)

• Quantification of gene expression (featureCounts or HTSeq)

• Differential expression analysis (DESeq2 or edgeR)

• Functional enrichment analysis (Gene Ontology, KEGG pathways)

• Regulatory network inference to identify co-regulated genes

Validation approaches:

• Confirm key differentially expressed genes via RT-qPCR

• Verify phenotypic changes predicted by transcriptomic alterations

• Complement with proteomics data when possible

• Perform targeted metabolomics to verify metabolic pathway changes

When interpreting results, consider that bacterial gene expression changes rapidly in response to environmental conditions, particularly during plant infection processes. Changes in genes involved in GABA catabolism, for example, have been observed in Pseudomonas syringae within the plant apoplast .

What statistical methods are most appropriate for analyzing PSPTO_2022 virulence assay data?

For bacterial entry and growth assays:

• Transform CFU data using log10 transformation to normalize distributions

• Apply appropriate statistical tests:

  • Two-sample comparisons: Student's t-test or Mann-Whitney U test

  • Multiple comparisons: ANOVA followed by post-hoc tests (Tukey's HSD, Bonferroni)

  • Repeated measures: Linear mixed models or repeated measures ANOVA

• Calculate effect sizes to determine biological significance beyond statistical significance

• Implement power analysis to ensure adequate sample sizes

For symptom severity assessments:

• Develop standardized scoring systems for consistent evaluation

• Use non-parametric tests for ordinal data (Mann-Whitney U, Kruskal-Wallis)

• Consider survival analysis methods for time-to-symptom development

• Implement bootstrapping or permutation tests for complex datasets

For multi-factor experiments:

• Design appropriate factorial experiments

• Use multi-factor ANOVA or generalized linear models to assess interactions

• Implement model selection procedures to identify important factors

In published research with similar Pseudomonas syringae proteins, statistical significance in bacterial entry assays was typically determined by comparing bacterial counts between wild-type and mutant strains at specific time points (e.g., 2 hours post-inoculation for entry, 6 days post-inoculation for virulence) .