KEGG: kpn:KPN_03576
STRING: 272620.KPN_03576
Translation initiation factor IF-2 in K. pneumoniae serves several essential functions in protein synthesis initiation:
Facilitates binding of formylmethionyl-tRNA (fMet-tRNA) to the 30S ribosomal subunit
Promotes formation of the pre-initiation complex
Assists in joining of the 50S ribosomal subunit to form the 70S initiation complex
Functions as a GTPase, providing energy through GTP hydrolysis
In K. pneumoniae, IF-2 shares significant homology with other Enterobacteriaceae members, particularly E. coli, though strain-specific variations may influence translation efficiency under different environmental conditions . The protein contains multiple domains including the G-domain responsible for GTP binding and hydrolysis, and domains involved in interactions with the ribosome and initiator tRNA.
When studying IF-2 across different K. pneumoniae pathotypes (classical vs. hypervirulent strains), researchers should implement:
Comparative sequence analysis of infB genes from well-characterized clinical isolates
Expression profiling of IF-2 under infection-relevant conditions using qRT-PCR and Western blotting
Ribosome profiling to identify translation patterns specific to each pathotype
Mutational analysis targeting key functional residues in different strain backgrounds
Experimental designs should account for the genetic distinctness of classical (cKp) and hypervirulent (hvKp) strains, which inhabit non-overlapping geographical regions and interact differently with host immune systems . A factorial experimental design (e.g., 2×2 or 3×3) can help evaluate multiple variables simultaneously, such as strain type, growth conditions, and stress responses . This approach allows assessment of how pathotype-specific differences in IF-2 might contribute to virulence traits.
For comprehensive IF-2 sequence analysis across K. pneumoniae isolates, researchers should employ:
| Analysis Type | Recommended Tools | Application |
|---|---|---|
| Multiple Sequence Alignment | MUSCLE, MAFFT, Clustal Omega | Identifying conserved domains and variable regions |
| Phylogenetic Analysis | RAxML, IQ-TREE, MrBayes | Evolutionary relationships among IF-2 variants |
| Structural Prediction | AlphaFold2, SWISS-MODEL | Modeling consequences of sequence variations |
| Horizontal Gene Transfer Detection | IslandViewer, Alien_Hunter | Identifying potential recombination events |
| Codon Usage Analysis | CodonW, GCUA | Examining translational selection pressures |
When analyzing sequence data, researchers should pay particular attention to:
Sequence variations between different sequence types (STs) and clonal complexes (CCs)
Comparison of strains with different antibiotic resistance profiles
Differences between isolates from various infection sites
Potential correlations between IF-2 sequence and virulence phenotypes
The growing genetic diversity observed in clinical K. pneumoniae isolates makes such comparative analysis particularly valuable for understanding potential adaptation mechanisms related to translation machinery.
The choice of expression system for recombinant K. pneumoniae IF-2 significantly impacts yield and protein quality:
| Expression System | Advantages | Disadvantages | Optimization Notes |
|---|---|---|---|
| E. coli BL21(DE3) | High yield, genetic similarity to K. pneumoniae, well-established protocols | Potential inclusion body formation | Use lower induction temperatures (16-25°C); co-express chaperones |
| E. coli Arctic Express | Enhanced protein folding at low temperatures | Lower expression levels, higher cost | Best for full-length IF-2 expression |
| Cell-free systems | Avoids toxicity issues, rapid production | Higher cost, limited scale | Useful for preliminary functional studies |
| Baculovirus-insect cell | Better folding of large proteins | Complex setup, longer production time | Consider for structural studies requiring high purity |
For optimal results with E. coli expression systems:
Use pET vectors with T7 promoter for high-level expression
Include an N-terminal His-tag for purification, with a TEV protease cleavage site
Optimize codon usage for rare codons in the IF-2 sequence
Test expression at multiple temperatures (16°C, 25°C, 37°C) and IPTG concentrations (0.1-1.0 mM)
Monitor growth curves during expression, as overexpression of translation factors can affect host cell growth
The genetic similarity between E. coli and K. pneumoniae makes E. coli an effective host for expression of K. pneumoniae proteins, though careful optimization is required for large translation factors like IF-2.
Purification of active recombinant IF-2 requires careful consideration of buffer conditions and chromatographic techniques:
Cell lysis considerations:
Use gentle lysis methods (e.g., lysozyme treatment followed by sonication)
Include protease inhibitors to prevent degradation
Maintain reducing conditions with DTT or β-mercaptoethanol (1-5 mM)
Optimized buffer composition:
Tris-HCl or HEPES buffer (pH 7.5-8.0)
Moderate salt concentration (150-300 mM NaCl)
Glycerol (10-15%) for stability
GTP or non-hydrolyzable analogs (0.1-1 mM) to stabilize native conformation
Multi-step chromatography approach:
Immobilized metal affinity chromatography (IMAC) using Ni-NTA for initial capture
Ion exchange chromatography to remove nucleic acid contaminants
Size exclusion chromatography for final polishing and buffer exchange
Critical quality controls:
SDS-PAGE and Western blotting to confirm identity and purity
Dynamic light scattering to assess aggregation state
GTPase activity assays to confirm functional integrity
Mass spectrometry to verify intact mass and post-translational modifications
Throughout purification, it's crucial to maintain GTP in the buffers as nucleotide binding significantly affects IF-2 stability and conformation. For structural studies, consider using stable GTP analogs like GDPNP to capture specific conformational states.
Distinguishing between native and recombinant IF-2 activity requires carefully designed controls and specific assay conditions:
GTPase activity assays:
Compare intrinsic GTPase rates using [γ-32P]GTP or malachite green phosphate detection
Measure ribosome-stimulated GTPase activity with purified ribosomes
Establish kinetic parameters (Km, kcat) for both native and recombinant proteins
Include negative controls with GTPase-deficient IF-2 variants (e.g., mutations in the G-domain)
Ribosome binding studies:
Filter binding assays with labeled ribosomes or labeled IF-2
Surface plasmon resonance to determine binding kinetics
Sucrose gradient centrifugation to assess 30S initiation complex formation
Competition assays between native and recombinant IF-2
In vitro translation systems:
Reconstituted translation systems depleted of endogenous IF-2
Complementation with either native or recombinant IF-2
Quantify translation of reporter constructs (luciferase, GFP)
Dose-response curves to determine relative activities
Differential labeling strategies:
Isotope labeling (15N, 13C) of recombinant protein for NMR studies
Fluorescent tagging at non-essential sites for microscopy and FRET assays
Mass spectrometry differentiation through incorporation of heavy isotopes
For all functional comparisons, it's critical to ensure equivalent active concentrations of proteins, which can be determined through active site titration assays using fluorescent GTP analogs or by measuring stoichiometric binding to ribosomes.
To effectively study infB gene regulation in K. pneumoniae, researchers should implement:
Promoter mapping and analysis:
5' RACE to identify transcription start sites
Reporter gene fusions (lacZ, gfp) to quantify promoter activity
Deletion and mutation analysis of promoter elements
ChIP-seq to identify transcription factor binding sites
Transcriptional regulation studies:
RNA-seq under various growth and stress conditions
qRT-PCR to validate expression changes
Northern blotting to identify operon structure and potential processing
Analysis of stringent response elements and their role in regulation
Post-transcriptional regulation investigation:
Ribosome profiling to measure translation efficiency
RNA structure probing of 5' UTR (SHAPE, DMS-seq)
Identification of potential small RNAs affecting infB expression
Assessment of mRNA stability under stress conditions
Integrative approaches:
Correlation of infB expression with virulence traits
Comparison between different K. pneumoniae pathotypes
Examination of infB regulation in antibiotic-resistant isolates
Global regulatory network mapping using systems biology approaches
The genetic context of infB in K. pneumoniae likely influences its expression patterns during infection and stress responses. Understanding these regulatory mechanisms could provide insights into how translation machinery adapts during pathogenesis and antibiotic exposure.
Investigating infB sequence variations in clinical K. pneumoniae isolates requires rigorous methodology:
Sample collection and processing:
Diverse sampling from different infection sites, geographical regions, and patient populations
Serial isolates from persistent infections to track evolutionary changes
Proper documentation of antibiotic treatment history and clinical outcomes
Consideration of within-patient genetic diversity as observed in clinical studies
Sequencing approach selection:
Sanger sequencing for targeted infB gene analysis
Whole genome sequencing for contextual genomic information
Deep sequencing to identify minor variants within populations
Long-read sequencing to resolve complex structural variations
Bioinformatic analysis pipeline:
Quality filtering and trimming of sequence data
Alignment against reference infB sequences
Variant calling with appropriate confidence thresholds
Annotation of functional impacts of amino acid substitutions
Validation and functional assessment:
PCR verification of key variants
Recombinant expression of variant IF-2 proteins
Functional comparison of variant proteins
Complementation studies in appropriate genetic backgrounds
Researchers should pay particular attention to sequence variations between different clonal complexes and sequence types, especially comparing ST258 (the predominant clone in many regions) with emerging non-CC258 sequence types that show increasing prevalence in clinical settings .
To investigate how mobile genetic elements affect infB gene function in K. pneumoniae, researchers should employ:
Genomic context analysis:
Whole genome sequencing to identify insertion sequences, transposons, or genomic islands near infB
Comparative genomics across multiple strains to identify variable regions
Analysis of sequence anomalies indicating horizontal gene transfer
Examination of specialized transduction events involving infB
Functional genomics approaches:
Transcriptome analysis to detect altered expression due to mobile element insertion
Transposon mutagenesis to identify regulatory elements
CRISPR-Cas9 editing to remove or modify mobile elements
Reporter systems to monitor effects on gene expression
Molecular characterization of recombination events:
Evolutionary analysis:
Phylogenetic reconstruction of infB evolution across K. pneumoniae lineages
Molecular clock analysis to date acquisition events
Selective pressure analysis (dN/dS ratios) to identify adaptive evolution
Correlation with antibiotic resistance acquisition timelines
Recent studies have shown that K. pneumoniae readily exchanges DNA with other members of the human microbiome and acquires mobile genetic elements carrying resistance and virulence genes . Understanding how these processes might affect translation factors like IF-2 could reveal mechanisms of adaptation during infection.
The potential contributions of IF-2 to K. pneumoniae virulence involve several mechanisms:
Stress adaptation during infection:
Modulation of translation initiation efficiency under host-imposed stresses
Selective translation of virulence factors and stress response proteins
Maintenance of protein synthesis under nutrient limitation
Adaptation to temperature shifts between environment and host
Pathotype-specific translation regulation:
Differential expression or activity between classical and hypervirulent strains
Potential role in translating hypervirulence-associated transcripts
Contribution to growth rate differences between pathotypes
Possible involvement in capsule production regulation
Immune evasion mechanisms:
Role in translating proteins involved in complement resistance
Support for rapid adaptation to macrophage and neutrophil encounters
Contribution to translation during phagosome residence
Potential role in biofilm formation through selective translation
Antibiotic stress responses:
Altered translation initiation under antibiotic exposure
Role in expressing resistance determinants
Recovery of translation after antibiotic-induced stress
Potential modifications affecting ribosome-targeting antibiotics
K. pneumoniae pathogenesis depends heavily on interactions between the bacterium and host immune defenses, including complement, macrophages, neutrophils, and monocytes . Translation machinery components like IF-2 likely play crucial roles in adapting to these host defenses and supporting the expression of virulence factors during infection.
Selecting appropriate experimental models for studying IF-2 during infection requires consideration of various factors:
In vitro cellular models:
Human lung epithelial cell lines for pneumonia models
Human bladder epithelial cells for urinary tract infection studies
Macrophage cell lines (THP-1, RAW264.7) for phagocytosis studies
Primary neutrophils for investigating bacterial survival
Ex vivo tissue models:
Precision-cut lung slices maintaining 3D architecture
Urinary tract epithelium explants
Human intestinal organoids for colonization studies
Whole blood assays for sepsis models
Animal infection models:
Mouse pneumonia models via intranasal infection
Urinary tract infection models via transurethral instillation
Liver abscess models for hypervirulent strains
Galleria mellonella (wax moth) for high-throughput screening
Specialized approaches for studying translation:
Ribosome profiling from infected tissues
Fluorescent reporters for translation monitoring in vivo
Selective capture of translated mRNAs (TRAP-seq)
Isotope labeling to track newly synthesized proteins
Each model has advantages for specific aspects of K. pneumoniae pathogenesis. For studying respiratory infections, models should reflect the interaction with respiratory epithelia, where K. pneumoniae fimbrial types play important roles in adherence . For hypervirulent strains, liver abscess models may be most relevant, while classical strains might be better studied in urinary tract or lung models.
To investigate host immune factor interactions with K. pneumoniae IF-2 during infection, researchers should employ:
Protein-protein interaction studies:
Co-immunoprecipitation of IF-2 from infected cells or tissues
Yeast two-hybrid screening against host factor libraries
Proximity labeling approaches (BioID, APEX) in infection models
Surface plasmon resonance with purified host factors and IF-2
Localization studies:
Immunofluorescence microscopy of IF-2 during infection
Live-cell imaging with fluorescently tagged IF-2
Electron microscopy with immunogold labeling
Subcellular fractionation of infected cells
Functional interaction assays:
Transfection of host cells with IF-2 to identify cellular responses
Screening for host factors affecting recombinant IF-2 activity
Competition assays with host translation machinery
Effect of host antimicrobial peptides on IF-2 function
Immunological approaches:
Analysis of antibody responses to IF-2 during infection
T cell epitope mapping of IF-2
Cytokine responses to purified IF-2
Inflammasome activation studies
These approaches could reveal whether IF-2 is recognized by host pattern recognition receptors or whether host defense mechanisms specifically target bacterial translation machinery. K. pneumoniae interacts with various components of the innate immune system , and understanding how translation factors participate in these interactions could provide new insights into pathogenesis.
Investigating IF-2 conformational dynamics presents significant technical challenges:
Structural biology approaches and limitations:
X-ray crystallography challenges: Capturing discrete conformational states requires stabilization with non-hydrolyzable GTP analogs and crystallization chaperones
Cryo-EM considerations: Large size and flexibility make particle classification complex; preferably studied in complex with ribosomes
NMR spectroscopy limitations: Full-length IF-2 exceeds size limits; domain-based approach necessary
Real-time conformational monitoring techniques:
Single-molecule FRET to track domain movements during GTP hydrolysis
Time-resolved small-angle X-ray scattering for solution-phase conformational transitions
Hydrogen-deuterium exchange mass spectrometry to map dynamic regions
Optical tweezers or atomic force microscopy for force-extension measurements
Computational approaches:
Molecular dynamics simulations of conformational transitions
Enhanced sampling methods to overcome energy barriers
Coarse-grained modeling of large-scale conformational changes
Integration of experimental constraints with simulation data
Experimental design considerations:
Time-resolved measurements synchronized with GTP hydrolysis
Stabilization of intermediate states with modified nucleotides
Strategic placement of fluorescent or spin labels at domain interfaces
Parallel analysis of wild-type and mutant proteins with altered conformational dynamics
These methodological challenges are significant but addressing them would provide valuable insights into how K. pneumoniae IF-2 functions mechanistically and potentially reveal species-specific features that could be exploited for targeted interventions.
Integrating multi-omics approaches for studying IF-2 in K. pneumoniae adaptation requires systematic methodology:
Comprehensive data collection strategy:
Genomics: WGS of isolates from various infection stages
Transcriptomics: RNA-seq under infection-relevant conditions
Proteomics: Global protein expression and post-translational modifications
Translatome: Ribosome profiling to capture translation dynamics
Metabolomics: Metabolic changes associated with translation regulation
Integration frameworks:
Correlation networks linking genomic variants to expression changes
Pathway enrichment across multiple data types
Machine learning approaches to identify patterns across datasets
Mathematical modeling of translation regulation in response to stress
Experimental validation pipeline:
Targeted mutagenesis of identified regulatory elements
Complementation studies with variant IF-2 proteins
Reporter systems monitoring translation of key transcripts
Time-course studies during infection progression
Clinical correlation approaches:
A key consideration is analyzing the data in the context of K. pneumoniae diversity, as studies have shown significant genetic diversity within patients, including multiple unrelated clones with different sequence types and resistance profiles . This complexity requires carefully designed sampling strategies and sophisticated computational approaches for data integration.
Evaluating IF-2 as a drug target against multidrug-resistant K. pneumoniae requires systematic experimental approaches:
Target validation strategy:
Conditional knockdown systems to demonstrate essentiality
Complementation studies with resistant mutations to identify mechanism
Comparative analysis across diverse clinical isolates
Assessment of impact on virulence in animal models
High-throughput screening approaches:
GTPase activity assays adapted to microplate format
Fragment-based screening with differential scanning fluorimetry
Structure-based virtual screening against binding pockets
Phenotypic screens with reporter strains
Compound evaluation framework:
Determination of minimum inhibitory concentrations (MICs)
Time-kill kinetics against different K. pneumoniae strains
Resistance development assessment through serial passage
Cytotoxicity testing in mammalian cell lines
Advanced drug development considerations:
Structure-activity relationship studies for lead optimization
In vitro ADME profiling (absorption, distribution, metabolism, excretion)
Animal pharmacokinetics and efficacy studies
Combination testing with existing antibiotics
Testing against diverse strains:
This experimental framework should be designed as a 2×3×4 factorial approach , where multiple variables (strain type, compound concentration, exposure time) can be systematically evaluated to develop a comprehensive understanding of compound efficacy against the diversity of K. pneumoniae strains encountered in clinical settings.