Recombinant Pseudomonas syringae pv. syringae Effector protein hopAB1 (hopAB1), partial

What is HopAB1 and what is its role in Pseudomonas syringae virulence?

HopAB1 (also known as VirPphA) is a type III effector protein secreted by Pseudomonas syringae through its type III secretion system. It belongs to a gene family whose founding member is HopAB2 from P. syringae pv. tomato . HopAB1 functions as a virulence factor that manipulates host defense mechanisms to promote bacterial infection. It was first identified as a virulence factor encoded on a large plasmid in P. syringae pv. phaseolicola 1449B (race 7) .

The protein has both virulence and avirulence functions, which are implemented through functional interactions with different host proteins . Unlike some other effectors that function as enzymes with specific biochemical activities (such as HopAF1, which has deamidase activity ), the exact biochemical mechanism of HopAB1 remains less characterized.

How does HopAB1 differ from other related effector proteins in the HopAB family?

HopAB1 is an allelic variant within the HopAB family, which includes HopAB2 (also known as AvrPtoB). Despite their sequence similarities, these proteins exhibit distinct functions:

The specific sequence differences between these allelic variants contribute to their different host specificities and functions. For instance, analysis of cherry-pathogenic P. syringae strains revealed that the loss of the avrPto/hopAB redundant effector group was observed in cherry-pathogenic clades, suggesting evolutionary adaptation to specific hosts .

What plant defense responses does HopAB1 typically trigger or suppress?

HopAB1 exhibits a dual role in plant defense responses depending on the host plant species and genetic background:

• Triggering defense responses: HopAB1 can elicit hypersensitive response (HR)-like necrosis on common bean and several nonhost plants when delivered via Agrobacterium systems . It also triggers HR in cherry leaves when ectopically expressed, confirming computational predictions about its avirulence function in certain hosts .

• Suppressing defense responses: As a virulence factor, HopAB1 can enhance gene silencing in Nicotiana benthamiana line 16C under conditions where it does not trigger HR . This suggests it may interfere with plant RNA silencing pathways that are important components of the plant immune system.

The dual functionality of HopAB1 reflects the complex evolutionary arms race between plants and pathogens, where effectors evolve to promote virulence while plants evolve recognition systems to detect these effectors and trigger immunity.

What are the most effective expression systems for producing recombinant HopAB1?

For recombinant expression of HopAB1, several systems have proven effective in research settings:

When designing expression constructs, it's important to consider potential post-translational modifications. Research has shown that some effectors from P. syringae, including those in the HopAB family, may undergo modifications such as myristoylation and palmitoylation . These modifications can affect protein localization and function.

Experimental protocol recommendations:

• For transient expression in plants, use pBIN-based vectors under the control of the 35S promoter

• Include appropriate epitope tags (HA, FLAG, or GFP fusion) for detection and localization studies

• Consider codon optimization for the expression system being used

• Include proper controls (empty vector, catalytic mutants) in all experimental designs

How can researchers effectively study HopAB1-host protein interactions?

Multiple complementary approaches can be employed to study HopAB1-host protein interactions:

• Yeast two-hybrid screening:

  • Useful for initial identification of interacting partners

  • Should be followed by in planta validation due to potential false positives

• Co-immunoprecipitation (Co-IP):

  • Express tagged versions of HopAB1 in plant tissue

  • Use specific antibodies to pull down protein complexes

  • Analyze by mass spectrometry to identify interacting partners

• Bimolecular fluorescence complementation (BiFC):

  • Fuse split YFP fragments to HopAB1 and candidate interactors

  • Co-express in plant cells and monitor for fluorescence reconstitution

  • Provides information on subcellular localization of interactions

• In vitro pull-down assays:

  • Express and purify HopAB1 with affinity tags (His, GST, MBP)

  • Incubate with plant protein extracts

  • Identify binding partners through Western blot or mass spectrometry

When designing these experiments, it's crucial to include proper controls such as unrelated effector proteins and catalytically inactive mutants of HopAB1. Similar approaches have been used successfully to identify interaction partners for other effectors like HopM1, which was shown to interact with several host proteins including MIN2/RAD23, MIN7/BIG5, MIN10/14-3-3ĸ, and MIN13/BIG2 .

What methods are most appropriate for analyzing HopAB1's effects on plant gene silencing?

Based on the research showing HopAB1's impact on gene silencing , the following methods are recommended:

• GFP silencing assay in N. benthamiana line 16C:

  • Co-express 35S::HopAB1 and 35S::GFP constructs via Agrobacterium infiltration

  • Monitor GFP fluorescence visually and quantitatively over time (3-7 days)

  • Include appropriate controls (empty vector, non-functional HopAB1 mutants)

• Northern blot analysis:

  • Extract total RNA from infiltrated leaf tissue

  • Probe for both mRNA and siRNA levels of the target gene

  • Quantify using densitometric analysis of specific Northern bands

• qRT-PCR analysis:

  • Design primers specific to target genes

  • Normalize expression to appropriate housekeeping genes

  • Compare expression levels between HopAB1-treated and control samples

• Small RNA sequencing:

  • For genome-wide analysis of HopAB1's impact on small RNA populations

  • Can identify specific miRNA or siRNA families affected by HopAB1

The experimental protocol should include viral silencing suppressors (such as P19 or HCPro) as positive controls for silencing suppression. Research has shown that when these viral suppressors are co-expressed with HopAB1, they block the GFP siRNA accumulation, indicating that the GFP silencing-enhancement phenotype induced by HopAB1 is silencing-dependent .

How can structure-function analysis be applied to understand HopAB1's molecular mechanisms?

Structure-function analysis of HopAB1 requires a systematic approach to identify key domains and residues responsible for its various activities:

• Structural prediction and modeling:

  • Use tools like AlphaFold, I-TASSER, or Phyre2 to predict protein structure

  • Compare with known structures of related proteins (e.g., HopAB2)

  • Identify potential functional domains and catalytic sites

• Site-directed mutagenesis:

  • Target conserved residues identified in structural analysis

  • Create single amino acid substitutions, especially in predicted active sites

  • Generate truncation mutants to identify minimal functional domains

• Functional assays for mutant proteins:

  • Test ability to trigger HR in resistant plants

  • Assess impact on bacterial virulence in susceptible plants

  • Examine effects on gene silencing in experimental systems

  • Evaluate protein-protein interactions with identified host targets

Important sites to consider based on research findings:

• N-terminal motifs potentially involved in myristoylation (Gly2) and palmitoylation (Cys5), which have been shown to be important for some HopAB family proteins

• Conserved residues shared with other HopAB family members

• Regions unique to HopAB1 compared to other family members

For example, research on related HopZ1 effectors has shown that mutation of the putative myristoylation site (G2A) and palmitoylation site (C5A) affects their ability to trigger cell death in plants . Similar approaches could be applied to HopAB1.

What are the current hypotheses about HopAB1's evolutionary history and host adaptation?

Current research suggests several key hypotheses about HopAB1's evolution:

• Convergent evolution in host adaptation:

  • Comparative genomics of P. syringae strains reveals convergent gene gain and loss associated with specialization onto specific hosts like cherry (Prunus avium)

  • Loss of the avrPto/hopAB redundant effector group was observed in cherry-pathogenic clades, suggesting evolutionary adaptation

• Horizontal gene transfer and phage-mediated acquisition:

  • Some effector genes like hopAR1 and hopBB1 were gained through putative phage transfer and horizontal transfer respectively

  • HopAB1 may have evolved similarly, being carried on a plasmid in P. syringae pv. phaseolicola

• Selective pressure from host recognition:

  • The diversification of HopAB family members likely reflects selective pressure from host recognition systems

  • This leads to an evolutionary arms race where effectors evolve to avoid recognition while maintaining virulence functions

Understanding these evolutionary patterns can provide insights into host range determination and the adaptation of pathogens to new hosts, which has important implications for agricultural disease management.

How does HopAB1 interact with the plant ethylene signaling pathway?

While the search results don't specifically address HopAB1's interaction with ethylene signaling, they do provide information about how another effector, HopAF1, targets this pathway . This offers a model for how type III effectors can manipulate plant hormone signaling:

• Targeting of biosynthetic enzymes:

  • HopAF1 targets methylthioadenosine nucleosidase proteins MTN1 and MTN2, enzymes in the Yang cycle essential for ethylene biosynthesis

  • By analogy, HopAB1 might target different components of the ethylene pathway

• Experimental approaches to investigate HopAB1-ethylene interactions:

  • Measure ethylene production in plants expressing HopAB1 using gas chromatography

  • Analyze expression of ethylene-responsive genes in the presence of HopAB1

  • Test genetic interactions between HopAB1 and ethylene signaling mutants

  • Perform targeted protein-protein interaction studies with ethylene pathway components

• Potential impact on plant defense:

  • Ethylene is a key hormone in plant defense responses

  • Manipulation of ethylene signaling could affect:

    • Programmed cell death and HR

    • Expression of pathogenesis-related genes

    • Systemic acquired resistance

To investigate these possibilities, researchers could employ a combination of genetic approaches (using ethylene signaling mutants), biochemical methods (protein-protein interactions), and physiological assays (measuring defense responses) to determine if and how HopAB1 affects ethylene-mediated immunity.

How should researchers interpret conflicting data about HopAB1 functions in different host systems?

When faced with conflicting data about HopAB1 functions across different experimental systems, consider the following analytical framework:

• Host genetic background effects:

  • HopAB1 may trigger HR in some plant species/varieties but not others

  • Analyze the presence/absence of specific resistance (R) genes in different hosts

  • Consider the evolutionary history of the plant-pathogen interaction

• Experimental delivery methods:

  • Different delivery methods (bacterial T3SS, Agrobacterium-mediated, direct protein application) may yield different results

  • Compare results across delivery methods while controlling for expression levels

  • Document protein localization for each delivery method

• Concentration-dependent effects:

  • Some effectors show different activities at different concentrations

  • Titrate expression levels to determine threshold effects

  • Use inducible expression systems to control protein levels precisely

When publishing results, clearly document all experimental conditions, genetic backgrounds, and protein expression levels to facilitate comparison across studies and resolution of apparent conflicts.

What statistical approaches are most appropriate for analyzing plant response data to HopAB1?

• For bacterial growth assays:

  • Transform CFU (colony-forming unit) data to log10 scale to normalize distribution

  • Use ANOVA followed by post-hoc tests (e.g., Tukey's HSD) for multiple comparisons

  • Include at least 3-4 biological replicates with 3 technical replicates each

  • Report means with standard errors or 95% confidence intervals

• For HR/cell death quantification:

  • Use ion leakage measurements for quantitative assessment

  • Apply appropriate transformations if data doesn't meet normality assumptions

  • Consider time-course experiments analyzed by repeated measures ANOVA

  • For visual HR rating, use non-parametric tests like Kruskal-Wallis

• For gene expression studies:

  • Use appropriate reference genes for qRT-PCR normalization

  • Apply the ΔΔCt method with statistical validation

  • For RNA-seq data, use specialized software (DESeq2, edgeR) for differential expression analysis

  • Control for multiple testing using Benjamini-Hochberg procedure

• For protein-protein interaction studies:

  • Quantify interaction strength using densitometry for co-IP experiments

  • Use appropriate controls for background binding

  • Consider statistical approaches for large-scale interactome data

When designing experiments, power analysis should be performed to determine appropriate sample sizes. For complex experiments with multiple factors, consider consulting with a statistician during experimental design rather than after data collection.

How can researchers distinguish between direct and indirect effects of HopAB1 on plant cellular processes?

Distinguishing direct from indirect effects of HopAB1 requires multiple complementary approaches:

• Temporal analysis:

  • Monitor responses at early time points after HopAB1 expression/delivery

  • Direct effects should be detectable before secondary responses occur

  • Use time-course experiments with high temporal resolution

• Direct biochemical interaction assays:

  • Perform in vitro binding assays with purified components

  • Use techniques like isothermal titration calorimetry (ITC) or surface plasmon resonance (SPR) to confirm direct interactions

  • Co-crystallization of HopAB1 with putative targets provides strong evidence for direct interaction

• Structure-function analysis:

  • Create HopAB1 variants with mutations in putative interaction interfaces

  • Test these variants for both binding to targets and downstream effects

  • Loss of both binding and function suggests direct effects

• Genetic approaches:

  • Express HopAB1 in plants lacking suspected direct targets

  • If effects persist, they may be mediated through alternative pathways

  • Using inducible expression systems in genetic knockout backgrounds can help resolve temporal aspects

For example, studies with other effectors like HopM1 have used biochemical purification of protein complexes formed in planta to identify direct interactors, revealing that HopM1 directly interacts with MIN7, MIN10, MIN13, and HLB1 to form a complex . Similar approaches could be applied to HopAB1 to distinguish its direct targets from downstream effects.

What are common challenges in expressing and purifying functional HopAB1, and how can they be addressed?

Researchers working with recombinant HopAB1 often encounter several challenges:

• Protein solubility issues:

  • Challenge: HopAB1 may form inclusion bodies in bacterial expression systems

  • Solutions:

    • Lower induction temperature (16-20°C)

    • Reduce IPTG concentration for induction

    • Use solubility-enhancing fusion tags (MBP, SUMO, TrxA)

    • Try specialized expression strains (e.g., Arctic Express, SHuffle)

• Protein stability problems:

  • Challenge: Purified HopAB1 may be unstable in solution

  • Solutions:

    • Screen different buffer conditions (pH, salt, additives)

    • Include protease inhibitors throughout purification

    • Store with glycerol (10-20%) at -80°C

    • Consider flash-freezing small aliquots to avoid freeze-thaw cycles

• Post-translational modifications:

  • Challenge: Bacterial systems may not provide plant-specific modifications

  • Solutions:

    • For studying myristoylation, use co-expression with N-myristoyltransferase

    • Consider using eukaryotic expression systems (insect cells, yeast)

    • Use plant-based expression systems for maximum authenticity

• Activity verification:

  • Challenge: Confirming that purified protein retains biological activity

  • Solutions:

    • Develop in vitro activity assays based on known functions

    • Compare activity of recombinant protein to native protein

    • Include positive controls in all functional assays

For challenging proteins like HopAB1, it may be necessary to accept lower yields of properly folded, active protein rather than pursuing maximum quantity at the expense of quality.

How can researchers optimize plant-based assays for studying HopAB1 functions?

Optimizing plant-based assays for HopAB1 requires attention to several key factors:

• Agroinfiltration optimization:

  • Challenge: Variable expression levels and plant responses

  • Solutions:

    • Standardize plant growth conditions (age, light, humidity)

    • Optimize bacterial OD600 for infiltration (typically 0.1-0.5)

    • Include positive controls (known elicitors) and negative controls (empty vector)

    • Consider co-infiltration with silencing suppressors when studying non-HR phenotypes

• HR and cell death assays:

  • Challenge: Subjective visual scoring of HR

  • Solutions:

    • Use objective quantification methods (ion leakage, Evans blue staining)

    • Standardize imaging conditions and analysis software

    • Implement blind scoring by multiple observers

    • Document time course of symptom development

• Subcellular localization studies:

  • Challenge: Overexpression artifacts in localization

  • Solutions:

    • Use native promoters when possible

    • Compare multiple epitope tags and fusion positions

    • Confirm localization using alternative methods (biochemical fractionation)

    • Consider the timing of observations (early vs. late)

• Gene silencing assays:

  • Challenge: Background variability in silencing systems

  • Solutions:

    • Use well-characterized reporter systems (e.g., N. benthamiana line 16C)

    • Include appropriate controls for silencing pathways

    • Quantify both transcript and small RNA levels by Northern blot

    • Consider developmental and environmental factors affecting silencing

When working with HopAB1, which can have both HR-inducing and gene-silencing effects depending on the context , it's particularly important to carefully control experimental conditions and timing of observations to distinguish between these potentially overlapping phenotypes.

What strategies can help resolve contradictory results in HopAB1 functional studies?

When faced with contradictory results in HopAB1 research, consider these systematic troubleshooting approaches:

• Independent verification with multiple techniques:

  • Challenge: Single assay systems may yield artifactual results

  • Solution: Confirm findings using complementary methodologies

    • Example: Verify protein interactions using both Y2H and Co-IP

    • Validate gene expression changes with both qRT-PCR and RNA-seq

• Control for protein expression levels:

  • Challenge: Expression level variations can cause different phenotypes

  • Solution: Implement systems with tunable expression

    • Use inducible promoters with dose-response testing

    • Confirm protein levels by Western blot in each experiment

    • Consider endogenous expression levels as reference points

• Genetic background considerations:

  • Challenge: Different plant genotypes may respond differently

  • Solution: Test multiple genetic backgrounds and document differences

    • Include relevant mutants affecting immunity pathways

    • Consider natural variation in host susceptibility

    • Use near-isogenic lines when available

• Experimental conditions standardization:

  • Challenge: Environmental conditions affect plant-pathogen interactions

  • Solution: Strictly control and document all variables

    • Plant age, growth conditions, time of day for experiments

    • Bacterial growth phase and concentration

    • Temperature and humidity during and after treatment

• Open data sharing and detailed methods reporting:

  • Challenge: Insufficient methodological details for reproduction

  • Solution: Document all experimental parameters in publications

    • Share detailed protocols through repositories

    • Report negative and contradictory results

    • Consider registered reports for contentious research areas

For example, when studying HopAB1's effect on GFP silencing, researchers found that the timing of observations was critical, with effects becoming apparent at 3 days post-infiltration . Similarly, when studying HR responses, the specific plant genotype and environmental conditions can significantly impact outcomes.