Recombinant Agrobacterium vitis Acetyl-coenzyme A synthetase (acsA), partial

What is Acetyl-coenzyme A synthetase (acsA) and what is its role in Agrobacterium vitis?

Acetyl-coenzyme A synthetase (acsA) is an enzyme that catalyzes the formation of acetyl-CoA from acetate, ATP, and coenzyme A. In bacteria including Agrobacterium vitis, this enzyme plays a critical role in central carbon metabolism, particularly in acetate utilization pathways. The enzyme is subject to posttranslational modifications that regulate its activity in response to changing physiological conditions . In A. vitis specifically, acsA may be involved in metabolic processes related to plant colonization and crown gall formation, though its precise role in pathogenicity remains under investigation.

How does posttranslational modification affect acsA activity?

Posttranslational modification represents an efficient mechanism for controlling enzyme activity in response to rapidly changing physiological conditions. In the case of acetyl-coenzyme A synthetase, its activity is regulated through acetylation and deacetylation. Research has demonstrated that protein acetyltransferases (such as AcuA) can acetylate acsA in an acetyl-CoA-dependent manner, while protein deacetylases (such as AcuC) can remove these acetyl groups . This reversible modification provides a rapid and energy-efficient way to modulate enzyme activity without requiring new protein synthesis or degradation.

What genetic engineering techniques are available for studying acsA in Agrobacterium species?

Several genetic engineering techniques have been developed specifically for Agrobacterium species, moving beyond traditional approaches that were cumbersome and time-consuming. Recent advances include recombineering systems based on phage recombinases obtained from Agrobacterium and related bacteria. Four pairs of RecET-like recombinases have been identified: RecETh1h2h3h4 AGROB6, RecETh1h2P3 RHI597, RecET RHI145, and RecETh RHI483 . These systems have been shown to work efficiently in different Agrobacterium strains, providing versatile tools for genetic manipulation including the study of acsA function through gene knockout, modification, or overexpression.

What are the basic experimental considerations when working with recombinant acsA from A. vitis?

When working with recombinant acsA from A. vitis, researchers should consider several key factors:

• Expression system selection: Recombineering systems with the pBBR1 origin have been found suitable for Agrobacterium species as they can stably replicate in these bacteria .

• Promoter choice: The tetracycline-inducible promoter (P tet) has shown to be highly stringent in Agrobacterium species, preventing undesired leaky expression that could affect experimental outcomes .

• Purification strategy: When isolating the recombinant protein, consider that acsA is subject to posttranslational modifications that may affect its activity.

• Activity assays: Develop assays that can distinguish between acetylated (less active) and deacetylated (more active) forms of the enzyme.

• Growth conditions: A. vitis growth conditions significantly impact metabolite profiles and potentially acsA expression and activity .

How can recombineering systems be optimized for acsA manipulation in different Agrobacterium strains?

Optimization of recombineering systems for acsA manipulation requires strain-specific approaches based on recent research findings. The efficiency of different recombinase systems varies significantly among Agrobacterium strains. For A. tumefaciens C58, the PluγET RHI145 system showed the highest efficiency, while for A. tumefaciens EHA105, the RecETh1h2h3h4 AGROB6 system performed best . For A. vitis specifically, researchers should test multiple recombineering systems to determine the optimal approach.

What is the relationship between acsA activity and metabolite profiles during A. vitis infection of grapevine?

The relationship between acsA activity and metabolite profiles during A. vitis infection involves complex metabolic shifts related to pathogenicity. GC-MS analysis of grapevine stem metabolites after A. vitis infection revealed 134 metabolites across various compound classes that were differentially clustered according to host response types . Multivariate analysis identified 11 metabolites that increased significantly in relation to infection response, primarily at post-inoculation stages rather than pre-existing in the host.

These metabolic changes were more prevalent (8 metabolites) at two days after inoculation than other stages, suggesting early metabolic responses are critical in determining infection outcomes . The metabolite profile changes were more strongly associated with susceptible responses (7 metabolites) than resistant (3 metabolites) or moderately resistant (1 metabolite) responses, indicating that many induced metabolites facilitate pathogen colonization and gall development.

Acetyl-coenzyme A synthetase likely plays a role in these metabolic shifts by affecting acetyl-CoA availability, which serves as a crucial intermediate in numerous metabolic pathways including those involved in defense responses and pathogen colonization.

How do posttranslational modifications of acsA affect Agrobacterium-plant interactions at the molecular level?

Posttranslational modifications of acsA, particularly acetylation/deacetylation, create a sophisticated regulatory mechanism that potentially influences Agrobacterium-plant interactions through several molecular pathways:

• Metabolic adaptation: By regulating acetyl-CoA production, acsA modification allows Agrobacterium to rapidly adapt its metabolism to the plant environment without requiring new protein synthesis.

• Virulence regulation: Acetyl-CoA is a precursor for various cellular processes including fatty acid biosynthesis and the tricarboxylic acid cycle, which provide energy and building blocks for bacterial growth during infection.

• Response to plant defense molecules: Plants produce various antimicrobial compounds during infection, including phenolic compounds like resveratrol . Regulation of acsA activity may help Agrobacterium respond to these defense molecules.

• Modulation of T-DNA transfer: The transfer of bacterial DNA to plant cells requires significant energy resources. Precise regulation of acetate metabolism through acsA modification could help balance energy allocation between growth and virulence functions.

• Biofilm formation: Acetyl-CoA-dependent pathways contribute to components needed for bacterial attachment and biofilm formation, which are critical for successful plant colonization.

What are the molecular mechanisms behind differential acsA expression in resistant versus susceptible grapevine species?

The molecular mechanisms governing differential acsA expression in resistant versus susceptible grapevine species likely involve complex host-pathogen signaling networks. Based on metabolite profiling studies, grapevine species show three distinct response types to A. vitis infection: resistant (RR), moderately resistant (SR), and susceptible (SS) . These response types correlate with different metabolite profiles.

In resistant varieties, the expression of stilbene compounds like resveratrol (a phytoalexin) may interact with bacterial gene expression programs, potentially suppressing acsA expression or activity . This hypothesis is supported by the observation that most disease-related metabolites are induced by pathogen infection rather than pre-existing in the host.

The plant host likely influences bacterial gene expression through:

• Defense-related signal molecules that directly or indirectly affect bacterial transcription factors

• Physical and chemical properties of the intercellular environment that trigger bacterial stress responses

• Availability of nutrients and cofactors necessary for optimal acsA function

• Competition with plant enzymes for acetate, affecting substrate availability for bacterial acsA

What expression systems are most effective for producing recombinant A. vitis acsA?

Based on recent research, several expression systems have proven effective for Agrobacterium proteins, with specific considerations required for acsA:

For acsA specifically, expression systems should accommodate the need to study posttranslational modifications. The tetracycline-inducible promoter (P tet) has demonstrated high stringency in Agrobacterium species, preventing leaky expression that could lead to undesired genetic changes or genomic instability . This controlled expression is particularly important when studying enzymes like acsA whose activity affects central metabolic pathways.

How can researchers effectively measure acsA activity in experimental settings?

Effective measurement of acsA activity requires methods that account for both total enzyme abundance and its posttranslational modification state:

• Spectrophotometric assays: Activity can be measured by coupling acetyl-CoA formation to other enzymatic reactions that produce detectable products. Common coupled assays include:

  • Malate dehydrogenase and citrate synthase coupling, measuring NADH oxidation

  • Pyruvate kinase and lactate dehydrogenase coupling, measuring AMP formation

• Direct assays: Measuring the rate of ATP consumption or CoA disappearance using HPLC or specialized reagents.

• Acetylation state determination:

  • Western blotting with anti-acetyllysine antibodies

  • Mass spectrometry to identify specific acetylated residues

  • Differential activity measurements before and after treatment with purified deacetylases

• In vivo activity assessment:

  • Growth rate comparison on acetate as sole carbon source

  • Metabolic flux analysis using labeled acetate

  • Measurement of downstream metabolite accumulation

When conducting these assays, researchers should control for:

• pH and temperature optimal for A. vitis acsA

• Potential inhibitors in the reaction mixture

• Stability of the enzyme during purification and storage

• Presence of required cofactors

What recombineering techniques are most suitable for acsA gene manipulation in A. vitis?

Based on comparative analysis of recombineering systems, researchers should consider the following approaches for acsA manipulation in A. vitis:

• RecET-like systems: The four identified RecET-like recombinase pairs (RecETh1h2h3h4 AGROB6, RecETh1h2P3 RHI597, RecET RHI145, and RecETh RHI483) offer promising options for acsA manipulation . For A. vitis specifically, empirical testing of each system would be necessary to determine optimal efficiency.

• Anti-recombination protein selection: The addition of Redγ or Pluγ can enhance recombination efficiency in some strains while decreasing it in others . For acsA manipulation, preliminary testing with both proteins would be advisable.

• Plasmid design considerations:

  • Use of pBBR1 origin for stable replication in Agrobacterium

  • P tet promoter for stringent control of recombinase expression

  • Appropriate selection markers for screening

• Homology arm design:

  • Length optimization (typically 40-50 bp minimum)

  • Avoidance of secondary structures

  • Consideration of GC content

• Transformation protocol:

  • Electroporation has shown the best efficiency for Agrobacterium species

  • Careful handling to maintain cell viability during the process

  • Recovery phase optimization

What experimental designs best elucidate the relationship between acsA activity and A. vitis virulence?

To effectively study the relationship between acsA activity and A. vitis virulence, researchers should consider multi-faceted experimental designs:

• Genetic manipulation approaches:

  • Creation of acsA knockout mutants using optimized recombineering systems

  • Development of point mutations affecting acetylation sites

  • Complementation studies with wild-type and mutant acsA variants

  • Construction of strains with constitutively active or inactive acsA

• Plant infection assays:

  • Green shoot cutting inoculation method as described in metabolite profiling studies

  • Measurement of gall severity through gall incidence (GI) and gall diameter (GD)

  • Classification of responses into resistant (RR), moderately resistant (SR), and susceptible (SS) types

  • Time-course experiments to capture early and late infection stages

• Metabolomics studies:

  • GC-MS analysis of both plant and bacterial metabolites during infection

  • Principal component analysis to correlate metabolite profiles with virulence

  • Targeted analysis of acetyl-CoA-dependent pathways

• Transcriptomics and proteomics approaches:

  • RNA-seq to identify genes co-regulated with acsA

  • Proteomics to determine acetylation states of acsA and other proteins

  • Integration of metabolomic, transcriptomic, and proteomic data

• In planta imaging:

  • Fluorescently tagged acsA to track localization during infection

  • Biosensors to measure acetyl-CoA levels in bacterial cells during plant colonization

How should researchers interpret changes in metabolite profiles related to acsA activity?

Interpreting changes in metabolite profiles related to acsA activity requires sophisticated analytical approaches and careful consideration of metabolic networks:

When analyzing metabolomic data, researchers should focus on:

• Temporal patterns: The timing of metabolite changes provides crucial information. Research has shown that 8 of 11 disease-related metabolites increased significantly at two days post-inoculation , suggesting early metabolic responses are critical in determining infection outcomes. For acsA-related studies, researchers should examine whether altered acsA activity affects the timing of these metabolic shifts.

• Response type correlations: Metabolite profiles cluster differently based on host resistance levels (RR, SR, SS) . When manipulating acsA, researchers should determine whether the resulting metabolite changes align more closely with resistant or susceptible profiles.

• Pathway analysis: Changes in acetyl-CoA-dependent pathways should be analyzed comprehensively, as acsA activity affects multiple downstream metabolic routes simultaneously. This includes:

  • Fatty acid biosynthesis

  • TCA cycle intermediates

  • Amino acid metabolism

  • Secondary metabolite production

• Integration with transcriptomic data: Changes in metabolite levels should be correlated with gene expression patterns to identify regulatory networks affected by acsA activity.

• Host-pathogen metabolic interactions: Distinguish between plant-derived and bacterial-derived metabolites, as both will be captured in whole-tissue analyses.

What statistical approaches are most appropriate for analyzing acsA expression and activity data?

Statistical analysis of acsA expression and activity data should be tailored to the experimental design and data characteristics:

• For time-course experiments:

  • Repeated measures ANOVA with appropriate post-hoc tests

  • Mixed-effects models to account for both fixed and random effects

  • Time-series analysis methods to identify patterns and trends

• For comparing multiple experimental conditions:

  • Factorial ANOVA with interaction terms to detect synergistic effects

  • Non-parametric alternatives (Kruskal-Wallis, Mann-Whitney) if normality assumptions are violated

  • Multiple comparison corrections (Bonferroni, Benjamini-Hochberg) to control false discovery rate

• For multivariate datasets (metabolomics, proteomics):

  • Principal Component Analysis (PCA) for dimension reduction and visualization

  • Partial Least Squares Discriminant Analysis (PLS-DA) for classification

  • Hierarchical clustering to identify patterns in complex datasets

  • ANOVA-simultaneous component analysis (ASCA) for analyzing designed metabolomics experiments

• For correlation analyses:

  • Pearson or Spearman correlation coefficients depending on data distribution

  • Network analysis to identify relationships between multiple variables

  • Path analysis to test causal relationships

• Sample size and power calculations:

  • A priori power analysis to determine appropriate sample sizes

  • Post-hoc power analysis to interpret negative results

How can researchers differentiate between direct and indirect effects of acsA manipulation on A. vitis virulence?

Differentiating between direct and indirect effects of acsA manipulation requires carefully designed experimental approaches and analytical strategies:

• Genetic complementation studies:

  • Wild-type complementation to confirm phenotype restoration

  • Point mutant complementation to identify specific functional domains

  • Heterologous complementation with acsA from related organisms

• Metabolic bypass experiments:

  • Supplementation with acetyl-CoA precursors or derivatives

  • Expression of alternative acetyl-CoA producing enzymes

  • Manipulation of downstream pathways to identify critical branches

• Temporal analysis approaches:

  • High-resolution time-course experiments to establish cause-effect relationships

  • Conditional expression systems to activate/deactivate acsA at specific infection stages

  • Correlation of acsA activity with virulence factor expression over time

• Omics data integration:

  • Multi-omics approaches combining transcriptomics, proteomics, and metabolomics

  • Network analysis to identify direct targets versus downstream effects

  • Causal modeling using structural equation models or Bayesian networks

• Comparative analysis across strains:

  • Examination of naturally occurring acsA variants with different activity levels

  • Correlation of acsA sequence/activity with virulence across multiple strains

  • Cross-species comparisons with related plant pathogens

What emerging technologies could advance the study of recombinant A. vitis acsA?

Several emerging technologies hold promise for advancing research on recombinant A. vitis acetyl-coenzyme A synthetase:

• CRISPR-Cas systems adapted for Agrobacterium species:

  • Development of Cas9 or Cas12 systems optimized for A. vitis

  • Base editing technologies for precise modification of acsA acetylation sites

  • CRISPRi/CRISPRa for tunable repression or activation of acsA expression

• Advanced protein structure determination:

  • AlphaFold2 and related AI approaches to predict acsA structure with high accuracy

  • Cryo-EM studies of acsA in different acetylation states

  • Hydrogen-deuterium exchange mass spectrometry to study conformational dynamics

• Single-cell technologies:

  • Single-cell RNA-seq to study heterogeneity in acsA expression during infection

  • Single-cell metabolomics to capture cell-to-cell variation in metabolic states

  • Spatial transcriptomics to map acsA expression patterns within infection sites

• Biosensors and in vivo imaging:

  • FRET-based biosensors for real-time monitoring of acsA activity

  • Acetyl-CoA biosensors to track metabolite dynamics during infection

  • Advanced microscopy techniques for tracking acsA localization and activity

• Synthetic biology approaches:

  • Orthogonal translation systems for incorporating non-canonical amino acids into acsA

  • Engineered posttranslational modification circuits for precise control of acsA activity

  • Minimal synthetic pathways to isolate and study essential acsA functions

How might understanding acsA regulation contribute to development of resistant grapevine varieties?

Understanding acsA regulation could significantly contribute to developing resistant grapevine varieties through several mechanisms:

• Biomarker identification:

  • Metabolites associated with acsA activity could serve as biomarkers for screening grapevine varieties

  • Early detection of susceptibility markers would accelerate breeding programs

  • Identification of compounds that naturally inhibit acsA could guide resistance breeding

• Targeted resistance strategies:

  • Engineering of grapevine varieties to produce natural acsA inhibitors

  • Development of decoy substrates that competitively inhibit acsA

  • Creation of plant variants that alter the intercellular environment to reduce acsA activity

• Resistance mechanism understanding:

  • Elucidation of how naturally resistant varieties affect bacterial metabolism

  • Identification of plant factors that promote protective acetylation of bacterial proteins

  • Understanding of metabolic cross-talk between plant and pathogen

• Screening tools development:

  • High-throughput assays based on acsA activity for screening germplasm collections

  • Molecular markers associated with ability to suppress acsA function

  • Predictive models relating plant metabolite profiles to potential resistance

• Translational applications:

  • Development of environmentally friendly treatments that target acsA activity

  • Creation of priming compounds that prepare plants to rapidly inhibit bacterial metabolism

  • Design of rootstock varieties with enhanced ability to suppress A. vitis colonization