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KEGG: lac:LBA1247
STRING: 272621.LBA1247
The dnaK gene in Lactobacillus acidophilus is organized in an operon structure that includes dnaJ, unlike some other lactobacilli where dnaJ is found elsewhere. Preliminary research indicates that in L. acidophilus CRL 639, the dnaJ gene is encoded in the same operon as dnaK . This genomic arrangement helps explain why dnaK and dnaJ are induced together under acid adaptation conditions, while in other lactobacilli, dnaJ has been found to be constitutively expressed . This organizational difference may contribute to the unique stress response mechanisms in L. acidophilus.
The co-expression pattern of these genes suggests a tightly regulated stress response system that may be advantageous for survival in acidic environments, which is particularly relevant for this organism's probiotic capabilities.
Acid adaptation in L. acidophilus induces the expression of both dnaK and dnaJ genes simultaneously . Low pH serves as an important signal for the induction of mechanisms that protect L. acidophilus against several environmental stresses . The acid-induced expression of DnaK contributes to the organism's ability to survive in acidic environments like the gastrointestinal tract.
Research methodologies to study this phenomenon typically involve:
Exposing L. acidophilus cultures to sublethal acidic conditions (pH 5.0-5.5)
Monitoring gene expression using qRT-PCR
Performing Western blot analysis to quantify protein levels
Comparing acid-adapted cells with non-adapted controls
Like other HSP70 family members, L. acidophilus DnaK typically contains:
An N-terminal nucleotide-binding domain (NBD) with ATPase activity
A substrate-binding domain (SBD) that recognizes hydrophobic peptide segments
A C-terminal lid domain that regulates substrate binding and release
These domains work together in an ATP-dependent cycle of substrate binding and release. Researchers investigating these domains should consider employing:
Multiple sequence alignment with characterized HSP70 family proteins
Homology modeling based on crystallized DnaK structures
Limited proteolysis experiments to identify domain boundaries
Mutational analysis of conserved residues in each domain
To effectively study the chaperone activity of recombinant L. acidophilus DnaK, researchers should consider:
In vitro assays:
Prevention of aggregation assay: Measure the ability of DnaK to prevent thermal aggregation of model substrates (e.g., luciferase, citrate synthase)
ATPase activity assay: Monitor ATP hydrolysis rates using colorimetric methods
Substrate binding assay: Use fluorescently labeled peptides to measure binding affinity
Protein refolding assay: Assess refolding of denatured proteins in the presence of DnaK
In vivo approaches:
Complementation studies in DnaK-deficient strains
Analysis of α-complementation of β-galactosidase, as demonstrated in E. coli DnaK studies
Example protocol for aggregation prevention assay:
Incubate substrate protein (0.5 μM) at 43°C in buffer containing ATP
Add various concentrations of purified DnaK (0-5 μM)
Monitor light scattering at 320 nm over 60 minutes
Calculate the percentage of aggregation prevention
| DnaK Concentration (μM) | % Aggregation Prevention | Relative Activity |
|---|---|---|
| 0 | 0 | 0 |
| 0.5 | 42 ± 5 | 0.42 |
| 1.0 | 68 ± 7 | 0.68 |
| 2.0 | 85 ± 4 | 0.85 |
| 5.0 | 95 ± 2 | 0.95 |
Note: Values represented are hypothetical examples based on typical chaperone assays
Temperature significantly impacts DnaK function, as evidenced by studies of DnaK in other bacteria. Drawing from E. coli research, we can infer that L. acidophilus DnaK likely exhibits temperature-dependent functional changes .
Methodological approaches:
Temperature-dependent ATPase activity assays (25-45°C range)
Circular dichroism spectroscopy to monitor structural changes
Differential scanning calorimetry to determine thermal stability
Binding affinity measurements at various temperatures
In vivo functional assays at different growth temperatures
Research on E. coli DnaK shows that in the dnaK756(Ts) mutant, α-complementation of β-galactosidase occurs at 30°C but not at higher temperatures (37°C or 40°C), even though these temperatures permit bacterial growth . Similar temperature-sensitive phenotypes could be investigated in L. acidophilus DnaK mutants.
Optimizing recombinant expression of L. acidophilus DnaK requires consideration of:
Expression systems:
Homologous expression in L. acidophilus using inducible promoters
Benefits: Proper folding, authentic post-translational modifications
Challenges: Lower yield, more complex genetic manipulation
Heterologous expression in E. coli
Benefits: High yield, established protocols
Challenges: Potential improper folding, inclusion body formation
Experimental conditions to optimize:
Temperature during induction (typically lower temperatures improve solubility)
Induction duration
Inducer concentration
Media composition
Co-expression with co-chaperones (DnaJ, GrpE)
Purification strategy:
Affinity chromatography using His-tag or other fusion tags
Ion exchange chromatography
Size exclusion chromatography for final polishing
Practical methodology:
Clone the L. acidophilus dnaK gene with appropriate tags
Transform into expression host
Screen multiple expression conditions using small-scale cultures
Analyze protein solubility and activity
Scale up production using optimized conditions
Implement multi-step purification protocol
Identifying DnaK-substrate interactions requires multiple complementary approaches:
In vitro methods:
Pull-down assays with immobilized DnaK
Cross-linking followed by mass spectrometry (XL-MS)
Surface plasmon resonance (SPR) for binding kinetics
Isothermal titration calorimetry (ITC) for thermodynamic parameters
Hydrogen-deuterium exchange mass spectrometry (HDX-MS)
In vivo approaches:
Co-immunoprecipitation followed by mass spectrometry
Bacterial two-hybrid assays
In vivo cross-linking and identification of complexes
Proximity-dependent biotin labeling (BioID)
Data analysis workflow:
Perform experiments under both normal and stress conditions
Identify enriched proteins by mass spectrometry
Validate key interactions with secondary methods
Categorize substrates by functional classification
Compare with known DnaK substrates from other organisms
Systematic mutagenesis approaches provide valuable insights into DnaK structure-function relationships:
Target selection strategies:
Conserved residues identified by multiple sequence alignment
Known functional residues from E. coli DnaK studies
Predicted active site and substrate-binding residues
Interface residues for co-chaperone interactions
Recommended mutation types:
Conservative substitutions (e.g., K→R) to probe electrostatic interactions
Non-conservative substitutions to disrupt function
Alanine scanning of binding interfaces
Domain deletion or swapping to assess domain autonomy
Functional assessment:
ATPase activity assays
Substrate binding assays
In vivo complementation of dnaK-deficient strains
Co-chaperone interaction studies
Thermotolerance tests
DnaK likely contributes significantly to L. acidophilus probiotic properties, particularly:
Stress resistance mechanisms:
Bile salt resistance
Oxidative stress protection
Temperature fluctuation adaptation
Host interaction aspects:
Potential immunomodulatory effects
Cellular adhesion to intestinal epithelium
Biofilm formation capabilities
Competition with pathogens
Research approaches to investigate:
Construction of DnaK-deficient or overexpression strains
Assessment of survival under simulated gastrointestinal conditions
Adhesion assays with intestinal cell lines
Immunomodulation studies with immune cells
Competition assays with pathogenic bacteria
In vivo colonization studies in animal models
The genome sequence of L. acidophilus NCFM revealed features that likely contribute to gastric survival and interactions with intestinal mucosa and microbiota , and DnaK may play a role in these functions.
In vitro protein folding assay protocol:
Denature substrate protein (e.g., luciferase) in 6M guanidinium-HCl
Dilute denatured protein into refolding buffer containing:
Purified L. acidophilus DnaK (0.5-5 μM)
DnaJ co-chaperone (0.1-1 μM)
GrpE nucleotide exchange factor (0.1-1 μM)
ATP regeneration system (phosphoenolpyruvate + pyruvate kinase)
ATP (2 mM)
Incubate at 30°C for defined time periods
Measure recovery of substrate protein activity
Compare with spontaneous refolding and with E. coli DnaK system
Data representation:
| Chaperone Components | Refolding Yield (%) | Refolding Rate (min⁻¹) |
|---|---|---|
| None (spontaneous) | 10 ± 2 | 0.005 ± 0.001 |
| DnaK only | 25 ± 4 | 0.012 ± 0.002 |
| DnaK + DnaJ | 48 ± 5 | 0.031 ± 0.004 |
| DnaK + DnaJ + GrpE | 72 ± 6 | 0.058 ± 0.005 |
| E. coli complete system (control) | 68 ± 5 | 0.054 ± 0.004 |
Note: Values represented are hypothetical based on typical chaperone-assisted protein folding assays
Comparative studies between L. acidophilus and E. coli DnaK can reveal:
Evolutionary conservation of chaperone mechanisms
Host-specific adaptations
Substrate specificity differences
Co-chaperone interaction preferences
Methodological approach:
Sequence and structural comparison
Multiple sequence alignment
Homology modeling
Conservation analysis of functional domains
Functional comparison
Substrate binding preferences
ATPase activity under various conditions
Complementation studies in dnaK-deficient strains
Chimeric protein analysis
Domain swapping between L. acidophilus and E. coli DnaK
Assessment of hybrid functionality
Evidence from E. coli suggests DnaK is necessary for α-complementation of β-galactosidase , providing a phenotypic assay that could be used to test the functional conservation of L. acidophilus DnaK.
Key design elements:
Promoter selection
Constitutive vs. inducible
Strength (high expression may lead to aggregation)
Host compatibility
Fusion tags
N-terminal vs. C-terminal placement
Tag size impact on folding and function
Cleavable vs. permanent tags
Common options: His6, GST, MBP, SUMO
Codon optimization
Match to expression host
Avoid rare codons
Consider mRNA secondary structure
Signal sequences
For secretion or surface display if needed
Native vs. heterologous signals
Vector backbone considerations
Copy number
Selection markers
Origin of replication
When creating recombinant L. acidophilus strains for surface display applications, selection of appropriate anchoring motifs significantly affects protein expression and localization, as seen in studies with other recombinant L. acidophilus proteins .
L. acidophilus DnaK has potential applications in vaccine development through several approaches:
As an adjuvant:
DnaK can enhance immune responses to co-delivered antigens
May promote both humoral and cellular immunity
Can be co-expressed with vaccine antigens in L. acidophilus
As a carrier protein:
Fusion of antigens to DnaK may increase immunogenicity
Can improve solubility and stability of problematic antigens
May facilitate antigen processing and presentation
As a vaccine delivery vehicle:
Recombinant L. acidophilus expressing DnaK-antigen fusions
Mucosal delivery to induce local and systemic immunity
Potential for oral vaccine formulations
Research on recombinant L. acidophilus strains has demonstrated the feasibility of displaying heterologous proteins on the cell surface using different anchoring motifs , a technology that could be adapted for DnaK-based vaccine applications.
Experimental approaches:
Growth curve analysis at various pH values
Compare wild-type, dnaK mutant, and complemented strains
Monitor growth kinetics using automated plate readers
Determine minimum pH for growth
Acid challenge survival assays
Expose cultures to lethal acid challenge (e.g., pH 2.0)
Enumerate survivors by plate counting
Calculate survival percentages
Gene expression analysis
qRT-PCR to quantify dnaK expression under acid stress
RNA-seq for global transcriptional response
Western blot for protein level confirmation
Acid adaptation studies
Pre-adapt cultures to mild acid stress
Challenge with severe acid stress
Assess protective effect of adaptation
Studies have shown that dnaK and dnaJ are induced together under acid adaptation in L. acidophilus , suggesting DnaK plays a crucial role in the acid tolerance response.
Computational methods:
Sequence-based prediction
Machine learning algorithms trained on known DnaK binding motifs
Scanning proteome for hydrophobic binding motifs
Considering protein disorder and accessibility
Structural bioinformatics
Homology modeling of L. acidophilus DnaK
Molecular docking with potential substrates
Molecular dynamics simulations of DnaK-substrate complexes
Network analysis
Protein-protein interaction predictions
Functional association networks
Co-expression data integration
Comparative genomics
Analysis across lactobacilli species
Identification of conserved DnaK-dependent pathways
Evolutionary analysis of substrate recognition
Implementation workflow:
Generate or obtain L. acidophilus DnaK structure
Identify binding pocket characteristics
Screen proteome for compatible binding motifs
Rank potential substrates by binding energy
Validate top predictions experimentally