Recombinant Salmonella paratyphi A 3-ketoacyl-CoA thiolase (fadI)

What is fadI and what is its primary function in Salmonella paratyphi A?

FadI is a 3-ketoacyl-CoA thiolase enzyme involved in the β-oxidation pathway in Salmonella paratyphi A. Its primary function is to participate in the degradation of fatty acids, specifically catalyzing the thiolytic cleavage of 3-ketoacyl-CoA into acyl-CoA and acetyl-CoA during anaerobic β-oxidation. FadI belongs to the family of degradative thiolases with broad chain length specificity, playing a parallel role to FadA which functions in aerobic β-oxidation of fatty acids . In S. paratyphi A, fadI contributes to fatty acid homeostasis which is critical for bacterial metabolism and potentially virulence during infection processes. The enzyme exhibits dual functionality – it can operate in both the degradative direction (breaking down fatty acids) and, surprisingly, can also function in the biosynthetic direction under certain conditions, catalyzing condensation reactions .

How does fadI differ from other thiolases in bacterial β-oxidation pathways?

FadI differs from other bacterial thiolases in several significant ways:

• Subcellular localization and oxygen requirements: While FadA functions in aerobic β-oxidation, FadI specifically operates in anaerobic β-oxidation pathways . This specialized role allows Salmonella to metabolize fatty acids under different environmental conditions.

• Substrate specificity profile: Unlike AtoB and YqeF which primarily exhibit high specificity for short-chain acyl-CoA substrates, FadI (along with FadA) possesses broad chain length specificity . This characteristic enables FadI to process various fatty acid lengths and types.

• Biosynthetic capabilities: Though primarily characterized as a degradative thiolase, FadI demonstrates unexpected biosynthetic potential. In vitro studies have shown that FadI can catalyze condensation reactions to form 3-ketoacyl-CoA and can even perform two rounds of iterative non-decarboxylative Claisen condensation reactions to produce α-pyrones .

• Regulatory control: The expression and activity of fadI appear to be under the control of the transcriptional regulator FadR, which responds to long-chain fatty acid (LCFA) levels and coordinates lipid homeostasis with other cellular functions .

What are the optimal expression systems for recombinant Salmonella paratyphi A fadI?

The optimal expression of recombinant S. paratyphi A fadI typically employs an E. coli-based expression system due to its genetic similarity to Salmonella and ease of genetic manipulation. Based on research methodologies:

Recommended expression protocol:

• Vector selection: pET-series vectors (particularly pET28a) with N-terminal His-tag for easy purification.

• Host strain: E. coli BL21(DE3) is preferred as it lacks certain proteases and contains the T7 RNA polymerase gene under IPTG control.

• Culture conditions:

  • Initial growth at 37°C until OD600 reaches 0.6-0.8

  • Induction with 0.5 mM IPTG

  • Post-induction cultivation at 18-25°C for 16-20 hours to enhance soluble protein expression

• Expression medium: LB or 2xYT supplemented with appropriate antibiotics has shown good results for thiolase expression, as demonstrated in studies of similar bacterial thiolases .

This system typically yields 10-15 mg of purified protein per liter of culture. Alternative expression systems such as cell-free protein synthesis may be considered for rapid screening of mutants but generally yield less protein.

What purification strategies yield the highest activity of recombinant fadI?

Purification of recombinant fadI should focus on maintaining protein stability and enzymatic activity. Based on successful approaches for similar thiolases:

Recommended purification protocol:

• Cell lysis: Sonication or French press in buffer containing 50 mM Tris-HCl (pH 8.0), 300 mM NaCl, 10% glycerol, and 5 mM β-mercaptoethanol.

• Initial purification: Immobilized metal affinity chromatography (IMAC) using Ni-NTA resin with an imidazole gradient (20-250 mM).

• Secondary purification: Size exclusion chromatography using Superdex 200 in buffer containing 25 mM HEPES (pH 7.5), 150 mM NaCl, and 1 mM DTT.

• Activity preservation measures:

  • Include 10% glycerol in all buffers to maintain protein stability

  • Add 1 mM DTT or β-mercaptoethanol to prevent oxidation of cysteine residues

  • Store purified enzyme at -80°C in small aliquots to avoid freeze-thaw cycles

This protocol has been shown to yield highly active thiolase enzymes (>95% purity) suitable for biochemical and structural studies . Similar thiolases purified this way retain their dual degradative and condensation activities.

What are the optimal assay conditions for measuring recombinant fadI activity?

The enzymatic activity of recombinant fadI can be measured in both the degradative (thiolytic) and synthetic (condensation) directions. Based on studies with similar thiolases:

Thiolytic direction assay (physiological direction):

• Buffer composition: 100 mM Tris-HCl (pH 8.0), 25 mM MgCl₂, 50 mM KCl

• Substrate: 3-ketoacyl-CoA (typically acetoacetyl-CoA for standardization)

• Cofactor: CoA (0.2-1 mM)

• Detection method: Spectrophotometric monitoring at 303 nm to follow the disappearance of the Mg²⁺-enolate complex of acetoacetyl-CoA

• Temperature and pH: Optimal activity at 30-37°C and pH 7.5-8.5

Condensation direction assay:

• Buffer composition: 100 mM potassium phosphate (pH 7.5)

• Substrates: Acetyl-CoA (0.5-2 mM) and various acyl-CoA compounds

• Detection method:

  • HPLC analysis of CoA derivatives formed

  • LC-MS detection of products like triacetic acid lactone (TAL) or other α-pyrones

• Temperature and pH: Optimal activity at 30°C and pH 7.0-7.5

Research has shown that FadI, like other thiolases, exhibits highest activity with acetoacetyl-CoA as starting substrate, with the reaction being approximately 20 times more efficient than when using only acetyl-CoA as substrate .

How does substrate specificity of fadI compare to other thiolases?

FadI demonstrates distinctive substrate specificity patterns compared to other thiolases:

Comparative substrate specificity profile:

*With limited substrates
+: low activity, ++: moderate activity, +++: high activity, -: negligible activity

FadI has broad substrate specificity similar to FadA but differs from AtoB and YqeF which are primarily specific for short-chain acyl-CoAs . FadI can utilize various acyl-CoA molecules as starting substrates, including acetyl-CoA, acetoacetyl-CoA, and other longer chain substrates. Unlike YqeF, which typically catalyzes only one round of non-decarboxylative Claisen condensation, FadI can perform up to two rounds of condensation, particularly with shorter chain substrates .

This versatility in substrate specificity makes FadI particularly interesting for biotechnological applications and may reflect its adaptive role in Salmonella metabolism under various environmental conditions.

How does fadI contribute to Salmonella paratyphi A metabolism and potential virulence?

FadI plays multiple roles in S. paratyphi A metabolism that may influence virulence:

• Energy production during infection: As part of the β-oxidation pathway, fadI enables Salmonella to utilize long-chain fatty acids (LCFAs) as carbon and energy sources, particularly under anaerobic conditions such as those found in the intestinal environment . This metabolic flexibility may provide a survival advantage during infection.

• Lipid homeostasis: By participating in fatty acid metabolism, fadI contributes to maintaining appropriate membrane lipid composition, which affects membrane fluidity, permeability, and the function of membrane-associated virulence factors .

• Metabolic adaptation: Studies in related Salmonella species indicate that LCFA metabolism contributes to colonization capabilities. Research in S. Typhimurium has shown that the LCFA metabolism-associated transcriptional regulator FadR contributes to gut colonization, with mutants showing competitive colonization defects . Given the similarity between S. Typhimurium and S. paratyphi A, fadI is likely part of this adaptive response.

• Potential biomarker role: Metabolomic studies of enteric fever caused by S. Typhi and S. paratyphi A have identified distinctive metabolite profiles, suggesting that altered metabolism, including fatty acid processing, may be associated with infection . These metabolites could include products of pathways involving fadI.

While direct evidence specifically linking fadI to S. paratyphi A virulence is limited in the provided search results, its role in fundamental metabolic processes suggests it may indirectly contribute to pathogenesis by supporting bacterial survival and adaptation during infection.

What is known about the relationship between fadI activity and host-pathogen interactions?

The relationship between fadI activity and host-pathogen interactions appears to involve several mechanisms:

• Metabolic adaptation to the intestinal environment: In studies of related Salmonella species, fatty acid metabolism enzymes including those in the fadI pathway allow bacteria to utilize nutrients available in the intestinal lumen. Research shows that LCFA may serve as an environmental cue for proper intestinal localization rather than primarily as an energy source .

• Impact on motility and colonization: In S. Typhimurium, disruption of fatty acid metabolism regulation (via fadR deletion) affects flagellar motility, which in turn influences gut colonization . While not directly demonstrated for fadI, as part of the regulated fatty acid metabolism network, fadI activity likely influences these processes.

• Contribution to metabolic signatures: Distinct metabolite profiles can separate S. Typhi cases, S. paratyphi A cases, and controls in human infections . These reproducible and serovar-specific systemic biomarkers detected during enteric fever may relate to altered activity of metabolic enzymes including fadI.

• Potential immunomodulatory effects: Changes in bacterial lipid composition resulting from altered fatty acid metabolism may affect recognition by host immune components and influence immune responses during infection, though specific evidence for fadI in this process is not detailed in the provided search results.

Research in S. Typhimurium suggests that LCFA metabolism is used as a significant signal rather than primarily as an energy source during intestinal infection . By extension, fadI's role in LCFA metabolism may contribute to this signaling process in S. paratyphi A, affecting host-pathogen interactions.

How can recombinant fadI be used for in vitro synthesis of bioactive compounds?

Recombinant fadI demonstrates significant potential for the in vitro biosynthesis of valuable bioactive compounds through its condensation activity:

• α-Pyrone synthesis: fadI can catalyze the formation of triacetic acid lactone (TAL) and other α-pyrones through iterative condensation reactions using acetyl-CoA and acetoacetyl-CoA as substrates . These α-pyrones serve as important scaffolds for various bioactive compounds including flavonoids, coumarins, and polyketides.

• Experimental protocol for α-pyrone synthesis using fadI:

  • Reaction components:

    • Purified recombinant fadI (5-10 μM)

    • Acetyl-CoA (1-2 mM) or acetoacetyl-CoA (0.5-1 mM)

    • Buffer: 100 mM potassium phosphate (pH 7.5)

    • Optional: Mg²⁺ (5 mM) to enhance activity

  • Reaction conditions: 30°C for 1-8 hours

  • Product detection: LC-MS or HPLC analysis

• Potential for producing diverse compounds: By varying the acyl-CoA starter units, fadI can potentially generate a range of modified α-pyrones. Research has shown that when provided with alternative acyl-CoA substrates such as benzoyl-CoA or hexanoyl-CoA, thiolases like fadI can produce various α-pyrone derivatives .

• Advantages over other biosynthetic approaches:

  • Non-decarboxylative Claisen condensation mechanism allows carbon chain extension without the requirement for carboxylated substrates

  • Simpler reaction conditions compared to type III polyketide synthases

  • Potential for one-pot enzymatic cascades combining fadI with CoA ligases and other modifying enzymes

These capabilities make fadI a valuable biocatalytic tool for synthetic biology applications focused on producing bioactive natural products and their derivatives.

What assay systems best detect fadI activity in experimental settings?

Several complementary assay systems can effectively monitor fadI activity, each with specific advantages depending on the research question:

1. Spectrophotometric assays for thiolytic activity:

• Principle: Monitors the decrease in absorbance at 303 nm corresponding to the disappearance of the Mg²⁺-enolate complex of acetoacetyl-CoA

• Advantages:

  • Real-time kinetic measurements

  • High-throughput capability

  • Quantitative data

• Limitations: Limited to acetoacetyl-CoA as substrate; potential interference from other compounds absorbing at similar wavelengths

2. Coupled enzyme assays:

• Principle: Links thiolase activity to NAD⁺/NADH conversion via coupling enzymes (e.g., β-hydroxyacyl-CoA dehydrogenase)

• Advantages:

  • Higher sensitivity than direct spectrophotometric methods

  • Can monitor reaction in physiologically relevant direction

  • Suitable for inhibitor screening

• Limitations: Potential interference from coupling enzyme inhibitors; requires additional reagents

3. LC-MS-based assays for condensation activity:

• Principle: Direct detection and quantification of CoA esters and α-pyrone products

• Advantages:

  • Definitive product identification

  • Ability to monitor multiple reactions simultaneously

  • Detection of novel products from various substrates

• Limitations: Lower throughput; requires specialized equipment

4. Radiometric assays:

• Principle: Uses ¹⁴C-labeled substrates to track product formation

• Advantages:

  • Extremely high sensitivity

  • Useful for detecting minor products

  • Less interference from contaminants

• Limitations: Requires radioisotope handling facilities; lower throughput

5. In vitro reconstitution system for polyketide formation:

• Principle: Combines fadI with substrate-generating enzymes (e.g., MatB and MatA for generating labeled acetyl-CoA)

• Advantages:

  • Models physiological context

  • Enables study of multi-enzyme reactions

  • Useful for determining substrate preferences

• Limitations: More complex setup; potential interactions between components

For most research applications, a combination of spectrophotometric assays (for rapid kinetic analysis) and LC-MS analysis (for definitive product characterization) provides the most comprehensive assessment of fadI activity.

How does fadI from S. paratyphi A compare to homologs in other Salmonella serovars?

Comparative analysis of fadI across Salmonella serovars reveals important similarities and differences:

Sequence conservation:

• High sequence homology (>95%) is typically observed between fadI enzymes from S. paratyphi A, S. Typhi, and S. Typhimurium, reflecting their evolutionary relatedness .

• The catalytic triad residues (Cys-His-Cys) essential for thiolase activity are completely conserved across all Salmonella serovars.

Functional differences:

• Despite high sequence similarity, fadI may contribute differently to pathogenesis in different serovars due to the distinct infection patterns: S. paratyphi A and S. Typhi cause systemic typhoid/paratyphoid fever, while S. Typhimurium typically causes localized gastroenteritis in humans .

• Metabolomic studies have demonstrated that S. Typhi and S. paratyphi A infections produce distinguishable metabolite profiles in infected individuals, suggesting potential differences in metabolic enzyme activities including those related to fatty acid metabolism .

Regulatory context:

• The regulation of fadI expression may differ between serovars due to variations in the FadR regulon and other transcriptional control mechanisms .

• In S. Typhimurium, FadR influences not only fatty acid metabolism genes but also flagellar motility genes, suggesting complex regulatory networks that may vary between serovars .

Clinical relevance:

• The distinct metabolite signatures produced during S. Typhi versus S. paratyphi A infections could potentially be exploited for diagnostic purposes, highlighting the importance of understanding serovar-specific metabolic activities .

• Different antimicrobial resistance patterns between serovars may influence treatment strategies, making serovar-specific enzymes potential targets for differential therapeutic approaches.

These comparative aspects are important for researchers developing serovar-specific interventions or diagnostic approaches based on metabolic differences between Salmonella variants.

What functional differences exist between fadI and other thiolases in Salmonella?

Within Salmonella, several thiolases exist with distinct functional characteristics:

Comparison of major thiolases in Salmonella:

Key functional differences:

• Metabolic context: While fadI operates in anaerobic β-oxidation pathways, fadA functions in aerobic fatty acid degradation . This complementary function allows Salmonella to process fatty acids under varying oxygen conditions, which is particularly important during infection as the bacterium encounters different microenvironments.

• Catalytic versatility: Though primarily characterized as a degradative enzyme, fadI demonstrates significant biosynthetic capability in vitro, catalyzing the formation of α-pyrones through condensation reactions . This unexpected biosynthetic potential distinguishes it from strictly degradative thiolases.

• Substrate handling: Research has shown that fadI, like fadA, can utilize a broad range of acyl-CoA substrates compared to more specialized thiolases . This versatility may contribute to Salmonella's metabolic flexibility during infection.

• Contribution to virulence: The different thiolases appear to have varying importance in virulence. In S. Typhimurium, deletion of fadBA (encoding fadA and fadB) did not affect gut colonization, while alteration of the regulatory network (via fadR deletion) did impact colonization . This suggests complex relationships between thiolase activity and virulence that may differ between enzyme types.

These functional differences highlight the specialized yet complementary roles of thiolases in Salmonella metabolism, with fadI occupying a distinct niche in anaerobic fatty acid processing that may be particularly relevant during certain stages of infection.

How can genomic and proteomic approaches advance our understanding of fadI function?

Advanced molecular approaches offer powerful tools for elucidating fadI function beyond traditional biochemical methods:

Genomic approaches:

• Comparative genomics: Analysis of fadI sequence conservation across Salmonella isolates from different clinical contexts can reveal adaptive mutations that correlate with virulence or metabolic capabilities. This could identify critical residues that distinguish S. paratyphi A fadI function from other serovars.

• Transcriptomic profiling (RNA-Seq): Comparing gene expression patterns between wild-type and fadI-deficient mutants under various conditions (aerobic/anaerobic, different carbon sources, infection models) can reveal the broader metabolic network influenced by fadI activity and identify co-regulated genes.

• ChIP-Seq analysis: This approach can map the binding sites of transcriptional regulators like FadR across the Salmonella genome, clarifying how fadI expression is controlled in relation to other metabolic genes and virulence factors .

• CRISPR-Cas9 screening: Genome-wide CRISPR screens can identify genetic interactions with fadI, revealing synthetic lethal relationships or compensatory pathways that become essential when fadI function is compromised.

Proteomic approaches:

• Interactome analysis: Proximity-labeling techniques (BioID, APEX) or co-immunoprecipitation coupled with mass spectrometry can identify proteins that physically interact with fadI, potentially revealing unexpected functional relationships.

• Post-translational modification mapping: Mass spectrometry-based approaches can identify PTMs on fadI that might regulate its activity or stability under different conditions, providing insight into activity control mechanisms.

• Thermal proteome profiling: This technique can monitor protein stability changes across the proteome in response to fadI inhibition or deletion, revealing downstream effects on metabolic enzymes and structural proteins.

• Protein localization studies: Advanced microscopy approaches combined with tagged fadI variants can reveal dynamic subcellular localization patterns that may change under different metabolic conditions or during infection.

These approaches, especially when integrated in a systems biology framework, can provide comprehensive understanding of how fadI functions within the complex network of Salmonella metabolism and virulence, potentially identifying new strategies for therapeutic intervention or diagnostic development.

What structural characteristics influence fadI substrate specificity and catalytic mechanisms?

The structural features of fadI play crucial roles in determining its substrate specificity and catalytic properties:

Key structural determinants of fadI function:

While detailed crystallographic data specifically for S. paratyphi A fadI is not presented in the search results, structure-function relationships can be inferred from studies of related thiolases. These structural insights provide a framework for understanding fadI's dual degradative and biosynthetic capabilities, which could be exploited for biotechnological applications.

How might fadI be exploited for biotechnological applications?

FadI possesses several properties that make it valuable for biotechnological applications:

Biocatalysis and chemical synthesis:

• Production of α-pyrones and related compounds: The ability of fadI to catalyze the formation of triacetic acid lactone (TAL) and other α-pyrones through iterative condensation reactions can be harnessed for green chemistry approaches to synthesize these valuable chemical scaffolds, which serve as precursors for pharmaceuticals, flavors, and fragrances.

• Designer polyketide synthesis: By leveraging fadI's broad substrate specificity and ability to accept various acyl-CoA starter units , researchers could develop enzymatic platforms for producing novel polyketide structures with potential bioactive properties.

• Chemo-enzymatic cascade reactions: FadI could be integrated into multi-enzyme cascades combining CoA ligases, reductases, and other modifying enzymes to create complex molecules from simple starting materials in one-pot reactions, offering advantages in stereoselectivity and reduced waste compared to traditional chemical synthesis.

Metabolic engineering applications:

• Enhanced fatty acid metabolism in industrial microorganisms: Recombinant expression of fadI could improve the capacity of industrial strains to utilize fatty acid-rich feedstocks or waste streams, potentially enhancing biofuel or biochemical production.

• Creation of novel metabolic pathways: FadI's ability to function in both degradative and biosynthetic directions provides opportunities for designing synthetic metabolic pathways that generate valuable compounds from inexpensive starting materials.

• Sensor development: The specificity of fadI for certain substrates could be exploited to develop biosensors for monitoring fatty acid metabolism or detecting specific acyl-CoA compounds in biological samples.

Challenges and research needs:

• Improving catalytic efficiency: Protein engineering approaches may be needed to enhance fadI's performance in specific applications, particularly to favor the biosynthetic direction for α-pyrone production.

• Stability enhancement: For industrial applications, increasing fadI's thermostability and solvent tolerance would be valuable research directions.

• Substrate and product range expansion: Further characterization of fadI's ability to accept non-natural substrates could open new applications in diverse chemical synthesis processes.

These biotechnological applications represent promising future research directions that build upon the fundamental understanding of fadI's catalytic versatility.

What are the critical research gaps in our understanding of fadI?

Despite progress in characterizing fadI, several critical knowledge gaps remain that warrant further investigation:

Fundamental knowledge gaps:

• Structural information: Detailed three-dimensional structures of S. paratyphi A fadI, particularly in complex with various substrates or inhibitors, would provide valuable insights into its catalytic mechanism and substrate specificity determinants.

• In vivo role during infection: While the search results provide information about LCFA metabolism in Salmonella gut infection , the specific contribution of fadI to S. paratyphi A pathogenesis remains to be fully elucidated through targeted studies.

• Regulatory networks: The complete regulatory network controlling fadI expression, including transcriptional, post-transcriptional, and post-translational mechanisms, requires further characterization to understand how its activity is coordinated with other metabolic pathways.

Methodological challenges:

• Development of specific inhibitors: High-specificity inhibitors targeting fadI without affecting human thiolases would be valuable research tools for dissecting its function in complex biological systems.

• In vivo activity assays: Methods to monitor fadI activity in living bacterial cells during infection would help clarify its role in pathogenesis.

• Improved heterologous expression: Optimizing expression systems for high-yield production of active recombinant fadI would facilitate both basic research and biotechnological applications.

Translational research needs:

• Diagnostic potential: The observation that S. Typhi and S. paratyphi A infections produce distinguishable metabolite profiles suggests potential for metabolic enzyme-based diagnostics, but direct links between fadI activity and specific biomarkers need to be established.

• Therapeutic targeting: Evaluation of fadI as a potential drug target requires better understanding of its essentiality under various infection conditions and the consequences of its inhibition on bacterial survival and virulence.

• Host-pathogen metabolic interactions: How fadI-mediated changes in bacterial metabolism influence host cell responses during infection remains poorly understood and represents an important area for future research.

Addressing these research gaps would significantly advance our understanding of fadI's biological significance and may lead to new strategies for detecting, preventing, or treating S. paratyphi A infections.

What approaches can effectively inhibit or modulate fadI activity for research purposes?

Several approaches can be employed to specifically inhibit or modulate fadI activity for research applications:

Chemical inhibition approaches:

• Small molecule inhibitors: While specific inhibitors for S. paratyphi A fadI are not extensively described in the provided search results, thiolase inhibitors typically include:

  • Thiol-reactive compounds that interact with the catalytic cysteine residues

  • CoA analogs that compete for the active site

  • Transition-state analogs that mimic the tetrahedral intermediate formed during catalysis

• Substrate/product analogs: Non-hydrolyzable analogs of acetyl-CoA or acetoacetyl-CoA can compete for binding without supporting catalysis, providing a means to selectively inhibit fadI activity.

• Mechanism-based inactivators: Compounds that initially bind as substrates but form covalent adducts with active site residues during the catalytic cycle can provide highly specific inhibition.

Genetic and molecular approaches:

• CRISPR-Cas9 gene editing: Precise modification of the fadI gene to introduce point mutations or deletions allows detailed structure-function studies and assessment of fadI's role in bacterial physiology and virulence.

• Antisense RNA and RNAi: In experimental systems where applicable, antisense strategies can reduce fadI expression levels without completely eliminating the enzyme, allowing examination of dose-dependent effects.

• Inducible expression systems: Placing fadI under control of inducible promoters enables temporal control of its expression, facilitating studies of its role in different phases of bacterial growth or infection.

• Dominant negative mutants: Expression of catalytically inactive fadI variants that can still form multimers with endogenous enzyme can disrupt native fadI function in a controlled manner.

Experimental considerations:

• Specificity validation: When using inhibitors, it's essential to confirm specificity by testing effects on related thiolases and other metabolic enzymes.

• Phenotypic verification: Changes in cellular fatty acid profiles, growth characteristics in different carbon sources, and virulence-associated phenotypes should be assessed to confirm functional consequences of fadI inhibition.

• Compensatory mechanisms: Research should consider potential metabolic rewiring or upregulation of alternative pathways that may occur in response to fadI inhibition, particularly in long-term experiments.

These approaches provide researchers with a toolkit for manipulating fadI activity to investigate its roles in bacterial metabolism, stress responses, and virulence.

How can isotope labeling experiments advance our understanding of fadI metabolic flux?

Isotope labeling approaches provide powerful tools for elucidating fadI's role in metabolic networks and quantifying flux through pathways involving this enzyme:

Strategic isotope labeling approaches:

• ¹³C-acetyl-CoA tracing experiments: Using ¹³C-labeled acetyl-CoA allows researchers to track carbon flow through fadI-catalyzed reactions. Studies have demonstrated that this approach can reveal substrate preferences of thiolases by analyzing the labeling patterns in products .

• Pulse-chase experiments: Sequential addition of labeled and unlabeled substrates can provide insights into the dynamics of fadI-catalyzed reactions, including substrate turnover rates and intermediate stability.

• Position-specific labeling: Using acetyl-CoA labeled at specific carbon positions enables detailed mapping of atom rearrangements during fadI-catalyzed reactions, confirming the mechanistic details of condensation or thiolysis reactions.

Advanced analytical platforms:

Research applications:

• In vitro mechanistic studies: Isotope labeling has revealed that FadI, FadA, and AtoB all mainly produce two-carbon-labeled triacetic acid lactones (TALs) when both ¹³C-acetyl-CoA and acetoacetyl-CoA are present, with only trace amounts of fully-labeled TALs generated from ¹³C-acetyl-CoA alone . This indicates a strong preference for acetoacetyl-CoA as starting units.

• Metabolic pathway elucidation: Isotope labeling can resolve the relative contributions of parallel pathways involving fadI and other thiolases in intact cells, clarifying their physiological roles.

• Host-pathogen metabolic interactions: During infection, labeled substrates can track how bacterial metabolism shifts in response to host environments and how enzymes like fadI contribute to these adaptations.

The enzyme MatB (malonyl-CoA synthetase) and MatA (malonyl-CoA decarboxylase) from Rhizobium leguminosarum have been successfully used to synthesize ¹³C-acetyl-CoA from ¹³C-malonate for such labeling experiments , providing a valuable methodological approach for researchers studying fadI.

How does fadI function integrate with broader metabolic networks in Salmonella?

FadI's activities are intricately connected with multiple metabolic pathways in Salmonella, creating a complex network of interactions:

Central metabolic connections:

• TCA cycle integration: The acetyl-CoA produced through fadI-catalyzed reactions feeds directly into the TCA cycle, connecting fatty acid metabolism with central carbon metabolism and energy production.

• Glyoxylate shunt interaction: During growth on fatty acids as carbon sources, the glyoxylate shunt becomes essential to conserve carbon atoms, creating a functional relationship between fadI-mediated β-oxidation and this anaplerotic pathway.

• Redox balance: The FADH₂ and NADH produced during fatty acid β-oxidation contribute to the cellular redox state, influencing numerous metabolic processes including respiration and biosynthetic reactions.

Regulatory cross-talk:

• FadR-mediated coordination: The transcriptional regulator FadR controls not only fatty acid metabolism genes but also influences other cellular processes including flagellar motility . This creates a regulatory link between fadI activity and bacterial motility, which affects virulence.

• Metabolic sensing: The products and substrates of fadI-catalyzed reactions may serve as metabolic signals that influence global regulatory networks. Long-chain fatty acids (LCFAs) have been shown to function as environmental cues for proper intestinal localization of Salmonella rather than merely serving as energy sources .

• Stress response connections: Fatty acid metabolism intersects with bacterial stress responses, with potential implications for adaptation to host environments during infection.

Pathogenesis-related connections:

• Lipid homeostasis and membrane function: By participating in fatty acid metabolism, fadI indirectly influences membrane lipid composition, which affects membrane properties and the function of embedded virulence factors.

• Metabolite production: The activity of metabolic enzymes including fadI contributes to the unique metabolite profiles that can distinguish between infections caused by different Salmonella serovars , indicating integration of fadI function with serovar-specific metabolic networks.

• Flagellar motility link: Studies in S. Typhimurium have revealed connections between fatty acid metabolism and flagellar motility , suggesting that metabolic enzymes like fadI indirectly influence critical virulence-associated behaviors.

This systems-level integration highlights how fadI functions beyond its immediate catalytic role, contributing to the complex adaptive capabilities of Salmonella during infection and environmental stress.

What computational modeling approaches can predict fadI behavior in different environments?

Computational modeling offers powerful approaches for predicting fadI behavior across various conditions:

Structural and mechanistic modeling:

• Molecular dynamics simulations: These can model fadI's interactions with diverse substrates, predicting binding affinities and catalytic efficiencies under different conditions. Simulations can reveal how temperature, pH, or mutations affect enzyme flexibility and substrate access.

• Quantum mechanics/molecular mechanics (QM/MM): For detailed catalytic mechanism modeling, QM/MM can simulate the electronic rearrangements during fadI-catalyzed reactions, predicting energy barriers and reaction rates for different substrates.

• Homology modeling and virtual screening: When crystal structures are unavailable, homology models based on related thiolases can facilitate virtual screening of potential inhibitors or substrate analogs, accelerating experimental design.

Systems-level modeling:

• Genome-scale metabolic modeling: Integration of fadI within genome-scale metabolic models of Salmonella enables prediction of metabolic flux distributions under different nutrient conditions, identifying conditions where fadI activity becomes particularly important.

• Flux balance analysis (FBA): This constraint-based approach can predict how fadI contributes to optimal growth or metabolite production under specific environmental conditions, identifying essential versus dispensable roles.

• Dynamic flux balance analysis: By incorporating time-dependent changes, these models can predict how fadI activity shifts during different growth phases or infection stages.

• Multi-scale models: Integration of molecular, cellular, and population-level models allows prediction of how molecular changes in fadI propagate to affect bacterial population dynamics during infection.

Machine learning applications:

• Substrate specificity prediction: Machine learning algorithms trained on biochemical data from multiple thiolases can predict fadI's activity on novel substrates, guiding experimental design for biocatalysis applications.

• Gene expression models: Neural networks incorporating transcriptomic data can predict how fadI expression changes across diverse environmental conditions, including those difficult to test experimentally.

• Host-pathogen interaction models: Agent-based models incorporating fadI-mediated metabolic capabilities can simulate bacterial behavior during host colonization, generating testable hypotheses about fadI's role in virulence.

Implementation considerations:

• Parameter estimation: Accurate modeling requires reliable kinetic parameters for fadI reactions, which should be experimentally determined under physiologically relevant conditions.

• Model validation: Predictions should be validated against experimental measurements, such as isotope labeling studies tracking metabolic flux through fadI-dependent pathways.

• Sensitivity analysis: This identifies which parameters most strongly influence model predictions, guiding experimental focus toward the most critical aspects of fadI function.

These computational approaches provide valuable frameworks for generating testable hypotheses about fadI behavior and for interpreting experimental results within the context of complex metabolic networks.