Recombinant Lactobacillus johnsonii Translation initiation factor IF-3 (infC)

What is the functional role of IF-3 in bacterial translation initiation?

Translation Initiation Factor IF-3 is an essential bacterial protein that enhances both the fidelity and speed of mRNA translation initiation. Functionally, IF-3 prevents premature 50S subunit association with the 30S ribosomal subunit and increases the rate of P site codon-anticodon interaction between fMet-tRNAfMet and the initiation triplet of mRNA . IF-3 consists of two domains (IF3C and IF3N) separated by a hydrophilic, lysine-rich linker that enables dynamic movement during the translation initiation process . By facilitating these fundamental steps, IF-3 controls the accuracy of translation start site selection and ensures proper protein synthesis.

How does the structure of IF-3 relate to its function in Lactobacillus species?

IF-3's structure directly supports its multifunctional role in translation initiation. The protein features two domains (IF3C and IF3N) that accommodate at varying velocities in response to binding of 30S ligands . In Lactobacillus species, this domain structure is particularly important as:

• The C-terminal domain (IF3C) primarily interacts with the P site of the ribosome

• The N-terminal domain (IF3N) creates a pocket for initiator tRNA acceptance

• The flexible linker between domains allows for the conformational changes needed during initiation

These structural elements contribute to IF-3's ability to act as a fidelity factor by increasing dissociation rates of non-canonical initiation complexes, a function critical in the high-fidelity translation systems observed in Lactobacillus species .

What makes L. johnsonii a suitable host for recombinant protein expression?

L. johnsonii offers several advantages as a recombinant protein expression system, particularly for therapeutic applications:

• As a commensal bacterium naturally found in vertebrate gastrointestinal and vaginal tracts, L. johnsonii has an established safety profile

• It demonstrates natural protective abilities against pathogenic bacteria, including E. coli strains, through multiple mechanisms

• L. johnsonii has been successfully engineered to express functional recombinant proteins, as demonstrated with GM-CSF expression systems

• It can survive and function in diverse host environments, making it suitable for in vivo applications

• The bacterium maintains immunomodulatory properties that can be beneficial when developing therapeutic proteins

For recombinant IF-3 expression specifically, L. johnsonii provides a gram-positive bacterial environment where the protein would be produced in a functionally similar context to its native state.

What are the methodological considerations for cloning the infC gene into L. johnsonii?

When cloning the infC gene into L. johnsonii expression systems, researchers should consider these key methodological approaches:

• Vector selection: Use specialized Lactobacillus expression vectors (such as pPG612 derivatives) with appropriate selection markers and Lactobacillus-compatible origins of replication

• Promoter optimization: Select promoters that function effectively in L. johnsonii, such as those demonstrated successful in the recombinant GM-CSF expression systems

• Codon optimization: Adjust the infC gene sequence to match L. johnsonii codon usage patterns for improved expression efficiency

• Signal peptides: Consider incorporating appropriate signal peptides if secretion of IF-3 is desired

• Transformation protocol: Use electroporation methods optimized for Lactobacillus species, with parameters typically including:

  • Voltage: 1.5-2.5 kV

  • Resistance: 200-400 Ω

  • Capacitance: 25 μF

  • Recovery media: MRS with 0.5M sucrose

• Verification strategies: Confirm successful cloning through PCR, restriction digestion, and sequencing before proceeding to expression analysis

How can expression of recombinant IF-3 in L. johnsonii be optimized?

Optimizing recombinant IF-3 expression in L. johnsonii requires systematic manipulation of several parameters:

• Induction conditions: If using an inducible system, determine optimal inducer concentration and timing through time-course experiments

• Growth phase manipulation: Test expression at different bacterial growth phases (early log, mid-log, late log) to identify peak production

• Media composition: Supplement standard MRS media with additional components based on this experimental design matrix:

• Temperature modulation: Lower growth temperatures (20-25°C) often improve protein folding and solubility compared to standard 37°C

• Oxygen levels: Test microaerobic versus anaerobic conditions to determine optimal environment for IF-3 production

• Co-expression of chaperones: Consider co-expressing molecular chaperones to improve proper folding of recombinant IF-3

The expression should be verified using Western blotting with appropriate antibodies, similar to the methods used to confirm the 15 kDa band seen in recombinant L. johnsonii expressing GM-CSF .

What are the challenges in purifying functional IF-3 from recombinant L. johnsonii?

Purifying functional IF-3 from recombinant L. johnsonii presents several challenges that researchers should address:

• Cell lysis optimization: L. johnsonii's gram-positive cell wall requires robust lysis methods:

  • Enzymatic digestion with lysozyme (10 mg/mL, 37°C, 1 hour)

  • Mechanical disruption via sonication or high-pressure homogenization

  • Combined approaches for maximum efficiency

• Solubility issues: IF-3 may form inclusion bodies. Strategies include:

  • Screening multiple lysis buffers with varying salt concentrations (100-500 mM NaCl)

  • Testing different pH conditions (pH 6.5-8.5)

  • Including stabilizing agents (5-15% glycerol)

• Maintaining domain integrity: Preserving the two-domain structure connected by a flexible linker is critical for function . Consider:

  • Avoiding harsh denaturants

  • Including protease inhibitors to prevent linker degradation

  • Using gentle purification techniques

• Purification strategy: A multi-step approach is recommended:

  • Initial capture via affinity chromatography (if tagged)

  • Ion exchange chromatography exploiting IF-3's basic properties

  • Size exclusion chromatography for final polishing

  • Activity testing at each stage

• Functional validation: Verify activity using in vitro translation assays measuring:

  • Prevention of premature 50S association

  • Enhancement of initiator tRNA binding

  • Discrimination against non-initiator tRNAs

How can dynamic FRET studies be designed to investigate the conformational changes of recombinant IF-3 in L. johnsonii?

Designing dynamic FRET (Förster Resonance Energy Transfer) studies to investigate conformational changes of recombinant IF-3 requires careful consideration of domain movement and labeling strategies:

• Strategic fluorophore placement: Based on the known domain structure of IF-3 :

  • Position donor fluorophore on IF3N domain

  • Position acceptor fluorophore on IF3C domain

  • Alternatively, use genetic incorporation of fluorescent unnatural amino acids

• Construct design considerations:

  • Introduce cysteine residues at non-conserved positions for maleimide-based labeling

  • Validate that mutations don't disrupt protein function using complementation assays

  • Consider using split fluorescent proteins as an alternative approach

• Experimental measurement parameters:

  • Use stopped-flow apparatus to capture rapid conformational changes

  • Record time-resolved FRET measurements during initiation complex formation

  • Compare dynamics with published velocities ranging over two orders of magnitude

• Analysis of domain movements:

  • Correlate FRET efficiency changes with different stages of initiation

  • Model the movement of IF3C toward the P site induced by IF1 and IF2

  • Measure transient accommodation of IF3N toward the 30S platform upon initiator tRNA selection

  • Track IF3C displacement from the P site during start codon decoding

• Validation approaches:

  • Perform parallel cryo-EM studies at different initiation stages

  • Compare results with molecular dynamics simulations

  • Correlate findings with biochemical assays measuring initiation complex formation

This approach would provide insights into whether IF-3 expressed in L. johnsonii exhibits the same dynamic properties as previously characterized in other bacterial systems.

What are the most effective methods for studying the interaction between recombinant IF-3 and the L. johnsonii ribosome?

To effectively study interactions between recombinant IF-3 and L. johnsonii ribosomes, researchers should employ these complementary methodologies:

• Ribosome profiling:

  • Isolate L. johnsonii ribosomes at different translation stages

  • Perform deep sequencing of ribosome-protected mRNA fragments

  • Map IF-3 binding sites through crosslinking and footprinting

  • Analyze with statistical models to determine binding preferences

• Cryo-electron microscopy:

  • Prepare samples of L. johnsonii 30S subunits bound to recombinant IF-3

  • Collect high-resolution images (preferably <3Å)

  • Process data to generate 3D reconstructions of the complex

  • Compare with published structures from model organisms

• Surface plasmon resonance (SPR):

  • Immobilize purified L. johnsonii 30S subunits on sensor chips

  • Measure binding kinetics (kon and koff) of recombinant IF-3

  • Determine equilibrium dissociation constants (KD)

  • Test effects of mutations on binding parameters

• Fluorescence-based assays:

  • Label IF-3 with environment-sensitive fluorophores

  • Monitor changes in fluorescence intensity or anisotropy upon ribosome binding

  • Perform competition assays with other initiation factors

  • Measure kinetics under different buffer conditions

• Comparative analysis:

  • Create a data integration table comparing L. johnsonii IF-3 binding parameters with those from other bacterial species:

How can we evaluate the potential of engineered L. johnsonii expressing modified IF-3 for enhancing the treatment of gastrointestinal infections?

Evaluating engineered L. johnsonii expressing modified IF-3 for treating gastrointestinal infections requires a multifaceted approach:

• In vitro competition assays:

  • Co-culture engineered L. johnsonii with gastrointestinal pathogens

  • Measure pathogen growth inhibition compared to wild-type L. johnsonii

  • Determine if modified IF-3 expression affects L. johnsonii's natural ability to prevent adhesion of diarrheagenic bacteria

• Cell invasion models:

  • Use intestinal epithelial cell lines (HT-29, Caco-2)

  • Compare prevention of pathogen adhesion between wild-type and engineered strains

  • Assess whether modified IF-3 affects S-layer protein function in inhibiting pathogen adhesion

• Immunomodulatory testing:

  • Measure cytokine production (IL-6, IL-1β, TNF-α) in response to engineered strains

  • Compare with the immunomodulatory effects observed with recombinant L. johnsonii expressing GM-CSF

  • Assess impact on inflammatory responses similar to protection seen against C. rodentium-induced colitis

• Animal model studies:

  • Design studies similar to those used for GM-CSF-expressing L. johnsonii

  • Evaluate colonization persistence in the GI tract

  • Measure markers of inflammation and infection severity

  • Compare with conventional antibiotic treatment approaches

• Translation to bovine applications:

  • Consider potential for treating bovine gastrointestinal infections

  • Build on findings from L. johnsonii used in bovine endometritis treatment

  • Develop appropriate delivery methods for farm application

What experimental models best demonstrate the efficacy of recombinant L. johnsonii expressing IF-3 variants compared to conventional therapies?

The most appropriate experimental models to demonstrate efficacy of recombinant L. johnsonii expressing IF-3 variants include:

• Mouse models of antibiotic-induced dysbiosis:

  • Induce dysbiosis with broad-spectrum antibiotics over 8 weeks

  • Compare recombinant L. johnsonii treatment to fecal microbiota transplantation

  • Measure restoration of immune cell populations (CD4+, CD8+, Tregs) in intestine and spleen

  • Assess IL-10 production maintenance, similar to previous L. johnsonii studies

• Pathogen challenge models:

  • Infect animals with clinically relevant pathogens (E. coli, Salmonella)

  • Compare multiple treatment groups:

    • No treatment (control)

    • Wild-type L. johnsonii

    • Recombinant L. johnsonii expressing IF-3 variants

    • Conventional antibiotic therapy

    • Combination approaches

  • Measure outcomes: survival, pathogen clearance, microbiome recovery, inflammation markers

• Ex vivo tissue cultures:

  • Use intestinal organoids derived from primary tissues

  • Challenge with pathogens in presence of different L. johnsonii strains

  • Assess epithelial integrity, tight junction proteins, and inflammatory responses

  • Evaluate cytokine profiles similar to those measured in endometritis studies

• Large animal models (for translational research):

  • Apply findings to bovine models building on endometritis research

  • Design protocols for administration via appropriate routes

  • Measure clinical outcomes relevant to veterinary applications

  • Compare with standard treatments used in agricultural settings

• Comparative efficacy metrics:

How should researchers address unexpected changes in translation efficiency when expressing recombinant IF-3 in L. johnsonii?

When facing unexpected translation efficiency changes in L. johnsonii expressing recombinant IF-3, researchers should implement this systematic troubleshooting approach:

What are the critical quality control metrics for evaluating functional activity of recombinant IF-3 produced in L. johnsonii?

To ensure recombinant IF-3 produced in L. johnsonii maintains proper functionality, researchers should apply these critical quality control metrics:

• Structural integrity assessment:

  • Circular dichroism to verify secondary structure composition

  • Thermal stability analysis to determine melting temperature

  • Size exclusion chromatography to confirm proper folding and oligomeric state

  • Mass spectrometry to verify full-length protein with correct modifications

• Domain interaction characterization:

  • FRET analysis to measure interdomain distances and dynamics

  • Limited proteolysis to assess domain boundary protection

  • Compare domain movement patterns with known velocities of IF-3 domains

• Functional assays:

  • 30S binding affinity determination (SPR or fluorescence anisotropy)

  • Initiator tRNA selection specificity (filter binding assays)

  • Prevention of premature 50S joining (light scattering or sucrose gradient)

  • Translation fidelity in reconstituted systems (measuring non-canonical start site usage)

• Comparative activity metrics:

  • Side-by-side testing with native IF-3

  • Preparation of activity calibration curves

  • Calculation of specific activity per mg of protein

• Standardized quality control table:

How might engineered L. johnsonii expressing modified IF-3 be combined with other recombinant approaches to create multifunctional therapeutic bacteria?

Creating multifunctional therapeutic bacteria by combining modified IF-3 expression with other recombinant approaches in L. johnsonii offers several innovative research directions:

• Dual expression systems:

  • Co-express modified IF-3 with immunomodulatory factors like GM-CSF

  • Design bicistronic or multi-cistronic expression cassettes

  • Implement orthogonal promoter systems for differential regulation

  • Determine optimal expression ratios through systematic testing

• Combinatorial therapeutic strategies:

  • Pair IF-3 variants with bacteriocins targeting specific pathogens

  • Co-express adhesion inhibitors to prevent pathogen colonization

  • Add enzymes that degrade inflammatory mediators, complementing the anti-inflammatory effects seen with GM-CSF expression

  • Incorporate biofilm-disrupting proteins for enhanced activity against biofilm-forming pathogens

• Regulatory circuit engineering:

  • Design sensing circuits that detect inflammation markers

  • Create feedback loops controlling expression based on environmental conditions

  • Develop kill-switches for controlled therapeutic duration

  • Implement colonization-dependent expression systems

• Delivery system optimization:

  • Develop encapsulation technologies to protect bacteria during transit

  • Engineer acid resistance mechanisms for improved gastric survival

  • Create adherence factors for targeted delivery to specific intestinal regions

  • Design controlled release mechanisms triggered by specific conditions

• Potential therapeutic combinations table:

What emerging technologies will advance our understanding of how recombinant IF-3 affects L. johnsonii's translational landscape?

Emerging technologies that will deepen our understanding of recombinant IF-3's impact on L. johnsonii's translational landscape include:

• Ribosome profiling with sub-codon resolution:

  • Apply nuclease footprinting with deep sequencing

  • Track ribosome positioning with single-nucleotide precision

  • Identify altered translation initiation patterns

  • Map the locations of ribosomes on transcripts genome-wide

• Single-molecule imaging in live bacteria:

  • Implement super-resolution microscopy techniques (PALM/STORM)

  • Track fluorescently tagged IF-3 molecules in real-time

  • Visualize interactions with ribosomes at single-molecule level

  • Correlate movement patterns with the known dynamic cycle of IF-3

• Cryo-electron tomography:

  • Image intact bacterial cells in near-native state

  • Visualize ribosomes in cellular context

  • Locate IF-3 binding within the complete cellular architecture

  • Compare wild-type and recombinant strain translation machinery organization

• Nanopore direct RNA sequencing:

  • Identify RNA modifications in real-time

  • Detect structural changes in mRNAs

  • Map translation initiation sites with greater precision

  • Correlate with altered IF-3 function

• Integrative multi-omics approaches:

  • Combine transcriptomics, proteomics, and metabolomics data

  • Generate comprehensive models of translation regulation

  • Apply machine learning to identify patterns of translation regulation

  • Create predictive models of how IF-3 variants affect global translation