Recombinant Agrobacterium vitis Glucose-6-phosphate isomerase (pgi), partial

What is the fundamental role of PGI in plant metabolism?

PGI isomerizes fructose 6-phosphate (F6P) and glucose 6-phosphate (G6P) in starch and sucrose biosynthesis pathways. In plants, both plastidic and cytosolic isoforms exist, with distinct regulatory properties. The plastidic PGI functions as an important regulatory checkpoint that restricts carbon flow and acts as a one-way valve preventing backflow of G6P into the Calvin-Benson cycle . This regulatory function ensures proper carbon partitioning between primary metabolism and storage compound synthesis.

How does Agrobacterium vitis differ from other Agrobacterium species?

Agrobacterium vitis was formerly classified as Agrobacterium tumefaciens biovar 3 but has been reclassified as a separate species. A. vitis strains are primarily associated with grapevines and are most frequently isolated from crown gall tumors on these plants . The Ti plasmid of A. vitis differs from A. tumefaciens in both the T-DNA and Vir regions . Most A. vitis strains are of the wide host range (WHR) type and can be classified into two groups based on their ability to utilize either octopine or nopaline as a sole carbon and nitrogen source .

Why is recombinant A. vitis PGI significant for plant research?

Research on recombinant A. vitis PGI provides insights into both bacterial metabolism and plant-pathogen interactions. Additionally, A. vitis could potentially serve as a more suitable transformation vector for Vitis species compared to A. tumefaciens . Understanding PGI function can also inform metabolic engineering strategies, as manipulating PGI activity has been shown to affect starch accumulation and degradation in plants .

What are the kinetic differences between plastidic and cytosolic PGI isoforms?

Studies with Arabidopsis PGI isoforms reveal significant differences in substrate affinity and regulation:

These differences reflect the distinct metabolic roles of the two isoforms and their integration into different cellular compartments and pathways.

How do metabolic intermediates regulate PGI activity?

Multiple metabolites affect PGI activity, with erythrose 4-phosphate (E4P) and 6-phosphogluconate (6PG) showing significant inhibitory effects:

E4P is particularly potent as a regulator, with inhibition constants in the low micromolar range, suggesting it serves as a key metabolic signal coordinating carbon flow between pathways .

What molecular mechanisms underlie the light/dark regulation of plastidic PGI?

The Km of spinach plastidic PGI for G6P increases by approximately 200% in dark-treated chloroplasts compared to light-treated ones, while the Km for F6P remains relatively stable . This selective modulation of substrate affinity effectively alters reaction directionality in response to light conditions. The molecular basis may involve:

• Redox regulation through thioredoxin-mediated disulfide bond modifications

• Allosteric regulation by metabolites that accumulate differentially in light/dark

• Post-translational modifications such as phosphorylation

• Protein-protein interactions that change with light conditions

This regulation helps coordinate carbon partitioning with photosynthetic activity.

What is the optimal protocol for measuring PGI enzyme activity?

The coupled spectrophotometric assay is the method of choice for measuring PGI activity, particularly for the F6P to G6P direction:

Reaction components:

• 50 mM bicine buffer pH 7.8

• 4.8 mM DTT

• 0.6 mM NADP+

• 2 U glucose-6-phosphate dehydrogenase (G6PDH) from Leuconostoc mesenteroides

• F6P (variable concentrations, 0-4.8 mM for Km determination)

• Purified PGI enzyme (typically 1-2 ng)

Measurement parameters:

• Monitor NADPH formation at 334 nm (subtract absorbance at 405 nm if using dual wavelength photometer)

• Use an extinction coefficient of 6190 M-1 cm-1 for NADPH

• Ensure linear product formation proportional to time and enzyme amount

• Verify coupling enzymes are not rate-limiting

This assay can be adapted to study inhibitors by including them at various concentrations and analyzing the kinetic data using appropriate models (Michaelis-Menten, Lineweaver-Burk, or Hanes-Woolf plots).

How can recombinant A. vitis PGI be effectively expressed in heterologous systems?

Based on successful approaches with other PGI variants, the following methodological framework is recommended:

For bacterial expression:

• Clone the A. vitis PGI gene into a pET-series vector with an N-terminal His-tag

• Transform into E. coli BL21(DE3) or similar expression strains

• Grow cultures at 37°C until OD600 reaches 0.6-0.8

• Induce with 0.1-0.5 mM IPTG

• Continue expression at lower temperature (16-20°C) for 16-20 hours

• Purify using Ni-NTA affinity chromatography followed by size exclusion chromatography

For plant expression:

• Create fusion constructs combining transit peptides (if targeting to plastids) with the PGI coding sequence

• Clone into a plant expression vector like pEAQ-HT-DEST1 containing the P19 suppressor of silencing

• Transform into Agrobacterium strain GV3101

• Infiltrate Nicotiana leaves with Agrobacterium at OD600 of 0.01-0.05

• Allow expression for 2-5 days post-infiltration

For plastid targeting, the transit peptide of Arabidopsis chloroplast PGI1 (first 144 bp starting at the ATG codon) has been successfully used .

What approaches can be used to study PGI regulation in vivo?

Several complementary approaches can be employed to study PGI regulation in living systems:

• Transgenic expression strategies:

  • Express modified PGI variants with altered regulatory properties

  • Target cytosolic PGI to plastids to disrupt normal regulation (shown to reduce starch accumulation by ~60%)

  • Use fluorescent protein fusions to monitor localization and expression levels

• Metabolic flux analysis:

  • Apply 13C labeling to track carbon flow through PGI

  • Compare wild-type and modified PGI expression lines

  • Correlate with starch accumulation and degradation patterns

• In vivo enzyme activity measurements:

  • Extract enzymes under non-denaturing conditions from light/dark-treated plants

  • Measure activity and kinetic parameters

  • Compare with recombinant enzyme behaviors

• Protein-protein interaction studies:

  • Use co-immunoprecipitation or yeast two-hybrid approaches

  • Identify regulatory proteins that interact with PGI

  • Correlate interactions with changes in enzyme activity

How should contradictory kinetic data for PGI from different sources be reconciled?

When faced with contradictory kinetic data for PGI from different species or strains, consider this analytical framework:

• Methodological considerations:

  • Examine differences in assay conditions (pH, temperature, buffer composition)

  • Evaluate protein preparation methods (tags, purification protocol)

  • Consider the presence of contaminating activities or inhibitors

• Biological context:

  • Different organisms may have evolved PGI variants with distinct regulatory properties

  • Light/dark growth conditions significantly affect plastidic PGI properties (Km for G6P increases 200% in dark)

  • Subcellular localization affects regulation (plastidic vs. cytosolic)

• Experimental validation:

  • Perform side-by-side comparisons under identical conditions

  • Test multiple substrate and inhibitor concentrations

  • Verify enzyme purity and integrity

• Data integration:

  • Develop a model that accounts for species-specific differences

  • Present data in standardized formats (e.g., tables comparing kinetic parameters)

  • Use structural information to explain functional differences

What statistical approaches are recommended for analyzing inhibition studies of PGI?

For robust analysis of PGI inhibition data, employ these statistical approaches:

• Inhibition model determination:

  • Generate Hanes-Woolf plots at different inhibitor concentrations

  • For E4P, verify competitive inhibition with G6P (except above 0.04 mM)

  • For 6PG, verify competitive inhibition with F6P (except above 1.0 mM) and non-competitive inhibition with G6P

• Ki value calculation:

  • Use secondary plots of slopes or intercepts vs. inhibitor concentration

  • Apply non-linear regression to directly fit to inhibition equations

  • Calculate 95% confidence intervals for all parameters

• Statistical validation:

  • Perform replicate experiments (minimum n=3)

  • Calculate standard errors for all parameters

  • Use F-tests to compare different inhibition models

• Data presentation:

  • Create inhibition constant tables (as shown below):

How can PGI manipulation be used to alter carbon partitioning in plants?

Targeted modification of PGI activity offers several approaches to redirect carbon flux in plants:

• Altering subcellular localization:

  • Targeting Arabidopsis cytosolic PGI to plastids of Nicotiana tabacum disrupts normal starch accumulation, reducing levels by approximately 60%

  • This confirms PGI's role as a rate-determining step in carbon partitioning

• Modifying regulatory properties:

  • Engineering PGI variants with altered sensitivity to inhibitors like E4P

  • Creating enzymes with modified Km ratios for G6P/F6P to favor specific reaction directions

  • Developing light/dark-insensitive variants to decouple from diurnal regulation

• Expression level manipulation:

  • Overexpression of native or modified PGI in specific tissues

  • Tissue-specific knockdown using RNAi or CRISPR approaches

  • Inducible expression systems to control timing of altered carbon flux

• Integration with other pathway modifications:

  • Combine PGI manipulation with changes in starch synthesis enzymes

  • Coordinate with modifications to Calvin-Benson cycle enzymes

  • Adjust transporters (like GPT2) to complement PGI alterations

Each approach must consider the one-way valve function of plastidic PGI that prevents backflow of G6P into the Calvin-Benson cycle .

What are the implications of A. vitis PGI for studying plant-pathogen interactions?

A. vitis PGI research provides unique opportunities for understanding plant-pathogen dynamics:

• Bacterial metabolism during infection:

  • PGI is essential for bacterial energy metabolism

  • Understanding how A. vitis adapts its carbon metabolism during infection

  • Identifying potential inhibitors that could disrupt bacterial metabolism without affecting plant PGI

• T-DNA transfer mechanisms:

  • A. vitis shows different T-DNA excision patterns compared to A. tumefaciens

  • T-DNA excision occurs after co-cultivation with grapevine tissues, but not with acetosyringone

  • PGI could potentially be linked to metabolic changes that affect transformation efficiency

• Host-specific adaptation:

  • A. vitis strains show specialization for grapevine hosts

  • PGI may have evolved unique properties adapted to the metabolic environment of grapevine tissues

  • Comparative studies with A. tumefaciens PGI may reveal adaptation mechanisms

• Transformation vector development:

  • A. vitis could potentially serve as a more suitable transformation vector for Vitis species

  • Understanding bacterial metabolism, including PGI function, may help optimize transformation protocols

  • Engineered A. vitis strains with modified PGI could potentially show enhanced transformation capabilities

How can researchers address low activity of recombinant A. vitis PGI?

When experiencing low activity with recombinant PGI, implement this systematic troubleshooting approach:

• Expression conditions optimization:

  • Reduce induction temperature (16-20°C)

  • Adjust inducer concentration (typically 0.1-0.5 mM IPTG)

  • Try different expression durations (4-24 hours)

• Buffer optimization:

  • Include reducing agents (4.8 mM DTT as used in validated assays)

  • Test different pH values around the optimum (pH 7.8 works well for many PGI assays)

  • Add stabilizing agents like glycerol (10-20%)

• Protein integrity verification:

  • Check for proteolytic degradation by SDS-PAGE

  • Verify correct folding using circular dichroism

  • Confirm primary sequence through mass spectrometry

• Activity assay refinement:

  • Ensure coupling enzymes are active (pre-test with standards)

  • Verify substrate quality and concentration

  • Check for the presence of inhibitors in the reaction mix

What strategies can resolve unexpected results in A. vitis transformation experiments?

For troubleshooting A. vitis transformation issues, consider this methodological approach:

• Bacterial strain verification:

  • Confirm opine utilization pattern of the A. vitis strain (octopine vs. nopaline)

  • Verify virulence on control plants

  • Check Ti plasmid integrity by PCR or restriction analysis

• Transformation conditions:

  • A. vitis shows different T-DNA excision patterns compared to A. tumefaciens

  • For A. vitis, T-DNA excision occurs after co-cultivation with grapevine tissues, not with acetosyringone (unlike A. tumefaciens)

  • Optimize OD600 of bacterial culture (0.01-0.05 works well for many applications)

• Host tissue considerations:

  • Use appropriate plant tissue (young, actively growing)

  • Consider plant defense responses

  • Verify compatibility between A. vitis strain and host species

• Construct design evaluation:

  • Check border sequences for integrity

  • Verify promoter activity in target tissue

  • Consider using the P19 suppressor of silencing to enhance expression

• Expression verification:

  • For fluorescent protein fusions, examine localization by microscopy

  • Perform enzymatic assays on plant extracts

  • Use RT-PCR or Western blotting to confirm transcription and translation