Recombinant Bacillus thuringiensis subsp. konkukian Phosphoenolpyruvate carboxykinase [ATP] (pckA), partial

Basic Research Questions

• What is Phosphoenolpyruvate carboxykinase [ATP] (pckA) and what is its role in Bacillus thuringiensis metabolism?

  Phosphoenolpyruvate carboxykinase (PEPCK or pckA) is a key metabolic enzyme that catalyzes the reversible decarboxylation of oxaloacetate to phosphoenolpyruvate (PEP) and carbon dioxide, with ATP as a phosphate donor. In B. thuringiensis metabolism, pckA plays crucial roles in:

  • Gluconeogenesis: Converting non-carbohydrate carbon sources to glucose

  • TCA cycle regulation: Maintaining balance of metabolic intermediates

  • Carbon flux distribution: Directing carbon between central metabolism and specialized functions

  • Sporulation metabolism: Supporting energy requirements during spore formation

  As illustrated in search result , pckA participates in metabolic changes associated with spore development, crystal protein formation, and mother cell lysis in B. thuringiensis. The enzyme is differentially regulated during various growth phases, with particular importance during nutrient limitation and sporulation when metabolic resources are being redirected.

• How does Bacillus thuringiensis subsp. konkukian differ from other Bt subspecies in terms of taxonomic classification?

  B. thuringiensis subsp. konkukian (serotype H34) has several distinctive features that differentiate it from typical insecticidal Bt strains:

  • Phylogenetic position: Analysis shows it is more closely related to B. cereus and B. anthracis than to typical insecticidal Bt strains

  • Clinical relevance: Unlike most Bt strains, subsp. konkukian was originally isolated from a human wound infection, demonstrating potential opportunistic pathogenic capabilities

  • Crystal protein profile: While classified as B. thuringiensis based on protein crystal production, its insecticidal activity profile differs from commercial Bt biopesticides

  • Genomic features: The pBT9727 plasmid in strain 97-27 shares significant homology with the pXO2 plasmid of B. anthracis

  Biochemical identification of B. thuringiensis subsp. konkukian reveals the following characteristic profile :

  Test	Result
  Catalase	Positive
  Oxidase	Negative
  Mobility	Positive
  Beta-hemolysis	Positive
  Maltose utilization	Acid production
  Glucose utilization	Acid production
  Galactose utilization	Negative
  Salicin utilization	Negative

• What methods are recommended for isolating and identifying Bacillus thuringiensis subsp. konkukian from environmental samples?

  Isolation and identification of B. thuringiensis subsp. konkukian involves a multi-step approach:

  1. Selective isolation:

     • Heat treatment (80°C for 10 minutes) to select for spore-forming bacteria

     • Growth on mannitol-egg yolk-polymyxin (MYP) agar

     • Incubation at 30°C for 24-48 hours

  2. Morphological characterization:

     • Gram-positive, rod-shaped cells with terminal spores

     • Phase-contrast microscopy to observe crystal inclusion bodies

     • Crystal protein verification using Coomassie brilliant blue staining

  3. Molecular identification:

     • PCR amplification of 16S rRNA genes

     • Specific detection of PlcR regulator gene with 100% sequence identity to Bt reference sequences

     • H-serotyping using specific antisera for flagellar antigens (H34)

     • Confirmation of absence of B. anthracis toxin genes (lef, cya, pagA) and capsule genes (capA-capC)

  4. Biochemical confirmation:

     • API 50-CHB and API 20E systems for biochemical profiling

     • Verification of key reactions (positive for catalase, negative for oxidase, acid production from maltose and glucose, negative for galactose and salicin)

  Definitive identification requires combining these approaches, with molecular techniques providing the highest specificity for subspecies determination.

Advanced Research Questions

• How does pckA modification affect spore development and crystal protein formation in recombinant Bt strains?

  Modification of pckA in recombinant B. thuringiensis strains significantly impacts both sporulation and crystal protein dynamics through alterations in central carbon metabolism:

  For sporulation:

  • The enzyme fulfills an unusual role in the final TCA cycle steps during sporulation

  • Disruption of pckA affects the metabolic balance in sporulating cells, potentially resulting in conditionally asporogenous phenotypes

  • Altered carbon flux affects the synthesis of dipicolinic acid (DPA) and other spore components

  For crystal protein formation:

  • pckA activity influences amino acid availability for crystal protein synthesis

  • Modified carbon flux can affect the timing of crystal protein accumulation relative to sporulation

  • In some cases, pckA modification can lead to overexpression of certain Cry proteins while reducing others

  The metabolic changes associated with sporulation are intricately connected to crystal protein formation and mother cell lysis. When pckA is modified, these processes become unbalanced, as demonstrated in studies of leuB mutants where expression of some cry genes is reduced while others (like Cry1Ac) may be overexpressed . Additionally, modified strains often show delayed or blocked mother cell lysis, which has implications for protein crystal release.

• What is the relationship between pckA expression and the PlcR virulence regulon in B. thuringiensis subsp. konkukian?

  The relationship between pckA and the PlcR virulence regulon in B. thuringiensis subsp. konkukian reveals important connections between metabolism and pathogenicity:

  1. The PlcR regulon:

     • Functions as a pleiotropic transcriptional activator regulating numerous virulence factors

     • Binds to a specific DNA sequence (PlcR box) in the promoter regions of target genes

     • Requires the product of the papR gene, which acts as a quorum-sensing effector

     • Significantly affects the pathogenicity of B. cereus and B. thuringiensis in both insects and mice

  2. pckA's integration with PlcR:

     • Metabolic enzymes like pckA support the energy requirements for virulence factor production

     • PlcR inactivation decreases the pathogenicity of B. thuringiensis, suggesting coordination with metabolic functions

     • In B. thuringiensis subsp. konkukian (which contains PlcR with 100% sequence identity to Bt reference sequences), pckA activity likely supports the metabolic demands of virulence factor production

  3. Functional evidence:

     • The disruption of PlcR considerably reduces the amounts of up to 56 exported proteins in B. cereus

     • Studies of B. thuringiensis virulence found that virulence was fully restored in complemented mutants for some PlcR-regulated genes, demonstrating their direct involvement in pathogenicity

     • Metabolic adaptations mediated by enzymes like pckA allow persistence in varied host environments

  This relationship is particularly significant in B. thuringiensis subsp. konkukian due to its closer relationship to pathogenic B. cereus than to conventional insecticidal Bt strains, making it an important model for studying virulence regulation in the B. cereus group.

• What approaches are most effective for creating marker-free modifications of pckA in Bacillus thuringiensis?

  Several advanced approaches have been developed for marker-free modifications of pckA in B. thuringiensis:

  1. Markerless gene deletion systems:

     • As demonstrated for leuB in B. thuringiensis, where a conditionally asporogenous recombinant strain was constructed

     • Employs counter-selectable markers (such as sacB conferring sucrose sensitivity)

     • Requires a two-step selection process allowing marker removal after confirmation of the desired modification

  2. CRISPR-Cas9 genome editing:

     • Design of guide RNAs specifically targeting pckA

     • Delivery of Cas9, guide RNA, and repair template via electroporation

     • Selection of edited strains through phenotypic screening

     • Note: CRISPR-Cas9 applications require Institutional Biosafety Committee (IBC) approval

  3. Cre-lox recombination system:

     • Integration of loxP sites flanking both the pckA target region and selection marker

     • Transient expression of Cre recombinase to excise the marker

     • Verification of marker removal via PCR and phenotypic testing

  4. Recombinant expression strategies:

     • For partial pckA expression, shuttle vectors like pHT3101 can be used under control of sporulation-specific promoters

     • After transformation by electroporation (20 KV/cm in a 0.2 cm-gap cuvette), transformants can be selected

     • Stability verification through subculturing for multiple generations is essential

  Each approach has specific advantages depending on the intended modification (point mutations vs. deletions) and strain characteristics. Transformants must be verified for both integration and stable inheritance through multiple generations to ensure experimental reliability.

Experimental Design Questions

• What considerations are critical when designing experiments to study pckA function in B. thuringiensis metabolism?

  Designing robust experiments to study pckA function requires attention to several critical factors:

  1. Genetic modification strategy:

     • Consider whether complete deletion, point mutation, or regulated expression is most appropriate

     • Include complementation controls to verify phenotypes are specifically due to pckA modification

     • Design constructs that maintain genomic context and native regulation where possible

  2. Growth condition selection:

     • Include both gluconeogenic (succinate, pyruvate) and glycolytic (glucose) carbon sources

     • Test multiple temperatures (particularly 25°C and 37°C) as enzyme activity and expression can be temperature-dependent

     • Consider both aerobic and microaerobic conditions to assess metabolic flexibility

  3. Temporal sampling design:

     • Sample across all growth phases (lag, exponential, transition, stationary, sporulation)

     • For sporulation studies, synchronize cultures to reduce heterogeneity

     • Include both short-term (minutes to hours) and long-term (days) analyses

  4. Multi-parameter analysis:

     • Combine transcriptomics, proteomics, and metabolomics approaches

     • Include enzyme activity measurements to correlate gene expression with function

     • Monitor physiological parameters (growth rate, sporulation efficiency, crystal protein production)

  5. Control implementation:

     • Wild-type strain grown under identical conditions

     • Empty vector controls for plasmid-based expression systems

     • Complemented mutant strains to verify phenotype restoration

     • Unrelated metabolic gene mutants to distinguish specific from general metabolic effects

  6. Data integration planning:

     • Design experiments to allow statistical correlation between multiple data types

     • Include sufficient replication (minimum three biological replicates)

     • Implement appropriate statistical design (randomization, blocking for batch effects)

  These considerations help ensure that experimental outcomes can be reliably attributed to pckA function rather than to secondary effects or experimental artifacts.

• What media compositions and growth conditions are optimal for studying pckA expression in B. thuringiensis?

  Optimizing growth conditions and media compositions is essential for meaningful pckA expression studies:

  1. Recommended media formulations:

     Media Type	Key Components	Application
     LB (Luria-Bertani)	Tryptone (10 g/L), Yeast extract (5 g/L), NaCl (10 g/L)	General cultivation and transformation
     PDA (Potato Dextrose Agar)	Potato extract (4 g/L), Dextrose (20 g/L)	Used for Bt growth in antagonism studies
     Sporulation medium	Nutrient broth with KCl, MgSO₄, Ca(NO₃)₂, MnCl₂, FeSO₄	Induction of sporulation
     Fermentation medium	For crystal protein production studies	Crystal protein expression
     Minimal medium	K₂HPO₄, KH₂PO₄, (NH₄)₂SO₄, MgSO₄·7H₂O, plus defined carbon source	Metabolic studies

  2. Carbon source selection:

     • For pckA induction: Succinate, malate, or pyruvate (gluconeogenic conditions)

     • For pckA repression: Glucose (when glycolytic pathways are predominant)

     • For differential analysis: Both glucose and a TCA cycle intermediate

  3. Critical growth parameters:

     • Temperature: 30°C optimal for growth; 25°C for phenotype expression in some cases

     • pH: 7.0-7.2 for optimal enzyme activity

     • Aeration: Shaking at 200-250 rpm for aerobic conditions

     • Culture vessels: Baffled flasks improve oxygen transfer

  4. Specialized conditions for specific analyses:

     • For sporulation studies: Nutrient depletion to synchronize development

     • For stress response analysis: Sub-lethal concentrations of osmotic (NaCl), oxidative (H₂O₂), or temperature stressors

     • For virulence studies: Host-mimicking conditions (serum supplementation, microaerobic conditions)

  5. Sampling timing:

     • For pckA transcriptional studies: Multiple time points spanning growth phases

     • For protein studies: Mid to late exponential phase and early stationary phase

     • For sporulation effects: Regular intervals from early stationary phase through spore maturation

  These conditions should be optimized for each specific strain, as genetic background can significantly influence optimal growth parameters and expression patterns.

• How can researchers effectively measure pckA enzyme activity in B. thuringiensis cell extracts?

  Measuring pckA enzyme activity in B. thuringiensis requires careful attention to extraction conditions and assay parameters:

  1. Cell extract preparation:

     • Harvest cells at desired growth phase (typically late exponential)

     • Wash cells with cold buffer to remove media components

     • Resuspend in extraction buffer: 50 mM HEPES (pH 7.5), 10 mM MgCl₂, 1 mM EDTA, 5 mM DTT, protease inhibitors

     • Disrupt cells by sonication or French press (keeping samples on ice)

     • Clarify by centrifugation (15,000 × g, 30 min, 4°C)

     • Assay immediately or store at -80°C with glycerol

  2. Spectrophotometric coupled enzyme assay:

     • Principle: Measure PEP formation from oxaloacetate by coupling to pyruvate kinase and lactate dehydrogenase, tracking NADH oxidation

     • Reaction mixture: 100 mM HEPES (pH 7.5), 10 mM MgCl₂, 10 mM MnCl₂, 2 mM ATP, 2 mM oxaloacetate, 0.15 mM NADH, 5 U pyruvate kinase, 5 U lactate dehydrogenase

     • Monitor decrease in absorbance at 340 nm (ε = 6,220 M⁻¹cm⁻¹)

     • Calculate activity as μmol NADH oxidized min⁻¹ mg⁻¹ protein

  3. Direct assay for reverse reaction:

     • Principle: Measure oxaloacetate formation from PEP and bicarbonate

     • Reaction mixture: 100 mM HEPES (pH 7.5), 10 mM MgCl₂, 2 mM PEP, 20 mM KHCO₃, 2 mM ADP

     • Couple to malate dehydrogenase reduction of oxaloacetate with NADH

     • Monitor decrease in absorbance at 340 nm

  4. qRT-PCR correlation:

     • While not a direct measure of enzyme activity, qRT-PCR of pckA can be correlated with enzyme activity measurements

     • Design primers specific to pckA as done for other metabolic genes in B. thuringiensis

     • Normalize to validated reference genes (such as 16S rRNA)

     • Compare expression patterns with protein levels and activity measurements

  5. Western blot analysis:

     • Use pckA-specific antibodies to quantify protein levels

     • Compare with enzyme activity to assess post-translational regulation

     • Include recombinant pckA standards for quantification

  6. Critical controls:

     • No-substrate control to measure background NADH oxidation

     • Heat-inactivated enzyme control

     • Specific inhibitor control (3-mercaptopicolinic acid)

     • Wild-type extracts as positive control

  This multi-method approach provides comprehensive characterization of pckA activity, enabling researchers to distinguish between transcriptional, translational, and post-translational regulation.

Data Analysis Questions

• How should researchers interpret contradictory results between transcriptomic and proteomic analyses of pckA expression?

  When faced with contradictory results between transcriptomic and proteomic data for pckA, researchers should implement a systematic analytical approach:

  1. Technical validation:

     • Confirm primer specificity for qRT-PCR through melt curve analysis and sequencing

     • Verify peptide uniqueness for proteomics through database searches

     • Perform technical replicates to assess measurement variability

     • Use alternative methods (Northern blots for RNA, Western blots for protein) to confirm findings

  2. Temporal dynamics analysis:

     • Consider time delays between transcription and translation

     • Implement time-course experiments with frequent sampling

     • Plot RNA and protein levels on the same timeline to identify lag periods

     • Examine the stability of both mRNA and protein under experimental conditions

  3. Post-transcriptional regulation investigation:

     • Analyze mRNA secondary structures affecting translation efficiency

     • Consider the role of small RNAs or antisense transcripts

     • Examine ribosome binding site accessibility

  4. Post-translational modification assessment:

     • Investigate potential protein modifications affecting stability or activity

     • Consider protein compartmentalization affecting extraction efficiency

     • Examine protein turnover rates through pulse-chase experiments

  5. Integration strategies:

     • Apply pathway analysis to identify regulatory patterns

     • Use correlation networks to find co-regulated genes

     • Implement mathematical models that account for regulatory delays

     • Consider the functional implications through enzyme activity assays

  In some experimental systems, good correlation between mRNA and protein levels can be achieved, as demonstrated in research showing "the expression patterns of mRNA were consistent with those of protein" for B. thuringiensis metabolic enzymes . When discordance persists, it should be viewed as biologically informative rather than problematic, potentially revealing novel regulatory mechanisms affecting pckA.

• What statistical approaches should be used to analyze pckA expression changes during Bt sporulation?

  Analyzing pckA expression during B. thuringiensis sporulation requires sophisticated statistical approaches:

  1. Time series analysis methods:

     • Smoothing techniques (LOESS) to reduce experimental noise

     • Change-point detection to identify significant transitions in expression

     • Autocorrelation analysis to identify cyclical patterns

  2. Differential expression analysis:

     • ANOVA with post-hoc tests for multi-timepoint comparisons

     • Linear mixed effects models to account for repeated measures

     • FDR correction for multiple testing (Benjamini-Hochberg procedure)

  3. Multivariate approaches:

     • Principal Component Analysis (PCA) to identify major sources of variation

     • Clustering methods (hierarchical, k-means) to group co-expressed genes

     • Heat maps with hierarchical clustering for visualization

  4. Correlation analysis:

     • Pearson or Spearman correlation between pckA and other genes

     • Time-lagged correlation to identify potential regulatory relationships

     • Partial correlation to control for confounding variables

  5. Expression pattern classification:

     • Compare pckA expression patterns to known sporulation regulators

     • Classify based on similarity to reference patterns (early, middle, late sporulation genes)

     • Evaluate coherence with other metabolic genes

  6. Data integration strategies:

     • Correlate gene expression with phenotypic measurements (sporulation rate, enzyme activity)

     • Integrate transcriptomic, proteomic, and metabolomic data

     • Implement network analysis to place pckA in broader regulatory context

  7. Specialized sporulation analysis:

     • Compare with expression profiles of known sporulation genes (spo genes, sigma factors)

     • Assess correlation with morphological changes

     • Evaluate temporal coordination with spore-specific metabolite production

  These statistical approaches help distinguish meaningful biological changes from experimental variation and place pckA expression changes within the broader context of the sporulation process.

• How can researchers differentiate between direct effects of pckA modification and indirect metabolic adaptations?

  Distinguishing direct pckA effects from adaptive responses requires a multi-faceted experimental strategy:

  1. Temporal resolution approaches:

     • Implement immediate sampling after inducible pckA modification

     • Use metabolic quenching techniques to capture instant metabolic states

     • Track metabolic flux changes over short time intervals (minutes to hours)

     • Compare with long-term adaptation patterns (days to weeks)

  2. Genetic complementation strategies:

     • Create a complemented ΔpckA strain expressing wild-type pckA

     • Develop point mutant variants with altered catalytic properties

     • Use inducible expression systems with varying expression levels

     • Compare phenotypes between deletion, complementation, and overexpression

  3. Metabolic network analysis:

     • Measure direct substrates and products of the pckA reaction

     • Assess changes in connected metabolic pathways

     • Implement 13C metabolic flux analysis to track carbon flow

     • Compare experimental results with metabolic model predictions

  4. Multi-strain comparative analysis:

     • Create multiple independent pckA mutants to identify consistent effects

     • Compare with mutations in other gluconeogenic enzymes

     • Analyze strains adapted to growth without pckA for compensatory mechanisms

  5. Regulatory network investigation:

     • Examine expression changes in known metabolic regulators

     • Identify co-regulated genes through transcriptome analysis

     • Map potential regulatory interactions affecting pckA expression

  6. In vivo validation techniques:

     • Test phenotypes under multiple growth conditions

     • Assess fitness in competition experiments

     • Evaluate performance in relevant biological contexts (sporulation, virulence)

  Through this comprehensive approach, researchers can build a causal model distinguishing primary effects of pckA modification from secondary adaptations, similar to the metabolic analysis approach used to characterize the role of leuB in B. thuringiensis sporulation .

Methodological Questions

• What protocol should be followed to create a recombinant B. thuringiensis strain with modified pckA?

  Creating a recombinant B. thuringiensis strain with modified pckA involves a series of precise molecular and microbiological steps:

  Materials needed:

  • B. thuringiensis subsp. konkukian culture

  • Appropriate shuttle vector (such as pHT3101 mentioned in result )

  • PCR reagents and primers specific for pckA

  • Restriction enzymes and DNA ligase

  • Transformation reagents (electroporation cuvettes, recovery media)

  • Selection media with appropriate antibiotics

  Protocol steps:

  1. Gene fragment amplification and construct preparation:

     • Design primers with appropriate restriction sites to amplify pckA with desired modifications

     • Amplify the pckA gene region from B. thuringiensis genomic DNA

     • Digest the PCR product and vector with appropriate restriction enzymes

     • Ligate the digested pckA fragment into the vector

     • Transform into E. coli for construct verification

  2. B. thuringiensis transformation:

     • Prepare electrocompetent B. thuringiensis cells from mid-log phase culture

     • Mix cells with 1-2 μg of purified plasmid DNA

     • Perform electroporation (5 ms at 20 KV/cm in a 0.2 cm-gap cuvette)

     • Recover in SOC medium at 30°C for 2-3 hours

     • Plate on selective media containing appropriate antibiotics

  3. Transformant verification:

     • Perform colony PCR to identify positive transformants

     • Extract genomic DNA and verify integration by PCR

     • Confirm stable maintenance by subculturing for three generations on selective media

     • Verify plasmid stability by subsequent growth on non-selective media followed by testing on selective media

  4. Expression verification:

     • Extract RNA and perform RT-PCR to verify transcription

     • Perform Western blotting to confirm protein expression

     • Measure enzyme activity to verify functional expression

  5. Phenotypic characterization:

     • Compare growth curves between wild-type and recombinant strains

     • Assess metabolic profiles using appropriate assays

     • Evaluate sporulation efficiency and crystal protein production if relevant

  This protocol can be adapted for different types of modifications, including gene deletion, point mutations, or expression of recombinant variants. For applications involving recombinant DNA and potentially pathogenic strains, appropriate biosafety considerations and institutional approvals should be obtained .

• What methods can be used to assess the impact of pckA modification on B. thuringiensis virulence?

  Assessing the impact of pckA modification on B. thuringiensis virulence requires multiple complementary approaches:

  1. In vitro virulence factor production:

     • Measure extracellular enzyme activities (proteases, lipases, hemolysins)

     • Quantify crystal protein production (Cry, Cyt toxins) by SDS-PAGE and Western blotting

     • Assess antifungal metabolite production through bioassays

     • Evaluate biofilm formation capacity

  2. Insect bioassays:

     • Conduct dose-response studies with target insects

     • Determine LC50 (median lethal concentration) and LT50 (median lethal time)

     • Compare wild-type and pckA-modified strains at multiple concentrations

     • Assess both larval and adult insect susceptibility

     • Use multiple infection routes (ingestion, cuticle contact)

  3. Cellular infection models:

     • Use insect cell lines to measure cytotoxicity

     • Assess bacterial adherence, invasion, and intracellular survival

     • Measure host cell cytokine/antimicrobial peptide responses

     • Evaluate resistance to cellular defense mechanisms

  4. Molecular virulence assessment:

     • Analyze expression of PlcR-regulated virulence genes

     • Measure crystal toxin gene expression and protein levels

     • Assess sporulation efficiency in relation to virulence

     • Monitor expression of InhA2 and other proteases involved in virulence

  5. In vivo infection models:

     • Galleria mellonella (wax moth) larvae model for systemic infections

     • Target insect species relevant to B. thuringiensis ecology

     • Compare infection progression between wild-type and modified strains

     • Assess bacterial persistence and dissemination in host tissues

  6. Competitive index studies:

     • Co-infect hosts with wild-type and pckA-modified strains

     • Determine relative fitness during infection

     • Use differentially marked strains for selection and quantification

  7. Virulence factor complementation:

     • Test whether virulence can be restored by complementation with wild-type pckA

     • Similar to the approach used for InhA2 in PlcR-deficient B. thuringiensis

     • Determine whether pckA overexpression can enhance virulence

  These methods collectively provide a comprehensive assessment of how pckA modification affects B. thuringiensis virulence through both direct metabolic effects and potential regulatory impacts on virulence factor production.

• What approaches are available to monitor the metabolic consequences of pckA modification in B. thuringiensis?

  Monitoring the metabolic consequences of pckA modification requires a multi-faceted approach:

  1. Growth phenotype characterization:

     • Measure growth rates on different carbon sources

     • Assess metabolic flexibility through carbon source utilization profiles

     • Determine biomass yield coefficients under various growth conditions

     • Evaluate stress tolerance (temperature, pH, osmotic pressure)

  2. Metabolite analysis:

     • Targeted metabolomics focusing on TCA cycle intermediates and gluconeogenic precursors

     • Untargeted metabolomics to identify unexpected metabolic changes

     • Intracellular metabolite extraction using cold methanol quenching

     • Quantification by LC-MS/MS or GC-MS methods

  3. Isotope tracer studies:

     • 13C-labeled substrate feeding experiments

     • Metabolic flux analysis to quantify carbon flow through central metabolism

     • Positional isotopomer analysis to determine pathway utilization

     • Dynamic labeling studies to assess metabolic turnover rates

  4. Enzyme activity measurements:

     • Assay activities of key enzymes in connected pathways

     • Monitor regulatory enzyme activities under different conditions

     • Compare in vitro enzyme kinetics between wild-type and modified strains

     • Measure allosteric regulation patterns of metabolic enzymes

  5. Global expression analysis:

     • Transcriptomics (RNA-seq) to identify compensatory gene expression changes

     • Proteomics to assess protein-level adaptations

     • Phosphoproteomics to identify changes in metabolic regulation

     • Integration of multi-omics data for comprehensive metabolic modeling

  6. Physiological response evaluation:

     • Monitor sporulation efficiency and timing

     • Assess spore properties (heat resistance, germination rates)

     • Evaluate crystal protein production and composition

     • Measure poly-3-hydroxybutyrate (PHB) accumulation

  7. Computational metabolic analysis:

     • Constraint-based metabolic modeling (flux balance analysis)

     • Metabolic control analysis to identify regulatory points

     • Network analysis to identify altered pathway utilization

     • Comparison with existing models of B. thuringiensis metabolism

  This comprehensive monitoring approach enables researchers to fully characterize how pckA modification ripples through the metabolic network of B. thuringiensis, affecting both core metabolism and specialized functions like sporulation and virulence factor production.