Recombinant Lactobacillus johnsonii Chaperone protein DnaK (dnaK), partial

What is the DnaK protein in Lactobacillus johnsonii and what is its primary function?

DnaK is a molecular chaperone protein belonging to the Hsp70 family that plays a central role in protein quality control systems within L. johnsonii. Its primary function is to act as a sensor for molecular stress by recognizing and binding to short hydrophobic stretches (approximately five residues long) in misfolded proteins . As part of the cellular protein quality control network, DnaK assists with the refolding of misfolded proteins, protects against irreversible aggregation, and can direct aberrant proteins for degradation . This chaperone is highly conserved across bacterial species and is essential for cellular homeostasis, particularly under stress conditions.

How is L. johnsonii DnaK different from DnaK proteins in other bacterial species?

While DnaK is structurally and functionally conserved across bacterial species, the specific DnaK protein in L. johnsonii contains sequence variations that distinguish it from other species. These variations can be used for taxonomic identification purposes . The dnaK gene has been successfully utilized as one of several housekeeping genes for phylogenetic analysis to differentiate Lactobacillus species, particularly within closely related groups . Additionally, comparative genomic studies of L. johnsonii strains have revealed host-specific variations that suggest co-evolution with their hosts, which may extend to differences in chaperone proteins like DnaK .

Why is recombinant L. johnsonii DnaK important for research purposes?

Recombinant L. johnsonii DnaK is valuable for research because it allows investigators to:

• Study the molecular mechanisms of protein quality control in probiotic bacteria

• Investigate host-microbe interactions, as DnaK may play a role in bacterial adaptation to specific hosts

• Develop methods for species identification and classification within the Lactobacillus genus

• Examine stress responses in bacteria, particularly in the context of the gut environment

• Explore potential immunomodulatory properties, as bacterial heat shock proteins can interact with the host immune system

Access to purified recombinant DnaK enables controlled experimental conditions that would not be possible when studying the native protein within bacterial cells.

What are the recommended methods for expressing and purifying recombinant L. johnsonii DnaK?

For successful expression and purification of recombinant L. johnsonii DnaK, researchers should consider the following methodology:

• Expression System Selection: E. coli BL21(DE3) is commonly used due to its high expression levels and lack of proteases. Codon optimization may be necessary as L. johnsonii has a lower GC content (34.91%) compared to E. coli.

• Vector Design: Incorporate a strong inducible promoter (such as T7) and add an affinity tag (His6 or GST) to facilitate purification. Consider adding a cleavage site for tag removal if the tag might interfere with functional studies.

• Culture Conditions: Grow cultures at 30°C rather than 37°C after induction to reduce inclusion body formation, as DnaK is involved in protein folding.

• Purification Protocol:

  • Lyse cells using sonication in buffer containing 20 mM Tris-HCl pH 8.0, 150 mM NaCl

  • For His-tagged protein, use Ni-NTA affinity chromatography

  • Further purify using size exclusion chromatography to remove aggregates

  • Consider including ATP in buffers (1-5 mM) to stabilize DnaK

• Quality Control: Verify purity using SDS-PAGE and Western blotting. Assess functionality through ATP hydrolysis assays and substrate binding experiments.

Remember to include protease inhibitors during lysis and purification steps, and maintain samples at 4°C throughout the process to minimize protein degradation.

How can I verify the functionality of purified recombinant L. johnsonii DnaK?

To verify that purified recombinant L. johnsonii DnaK is functionally active, several complementary assays should be performed:

• ATP Hydrolysis Assay: DnaK has intrinsic ATPase activity that can be measured using colorimetric assays (e.g., malachite green) or radioactive assays with [γ-32P]ATP. The activity should increase in the presence of co-chaperones and substrates.

• Substrate Binding Assay: Measure binding to model substrates such as fluorescently labeled peptides containing hydrophobic motifs. Since DnaK binds to hydrophobic stretches approximately five residues long , peptides with this characteristic can be used to test binding affinity.

• Protein Aggregation Prevention Assay: Test the ability of DnaK to prevent aggregation of model substrates like citrate synthase or luciferase under heat stress conditions, monitoring by light scattering.

• Circular Dichroism (CD) Spectroscopy: Verify proper folding of the recombinant protein and assess thermal stability.

• Co-chaperone Interaction: Examine interactions with known co-chaperones like DnaJ and GrpE using pull-down assays or surface plasmon resonance.

Functional DnaK should demonstrate ATP-dependent binding and release of substrate proteins, with binding affinity changing according to its nucleotide-bound state (ATP vs. ADP).

What are the best approaches for studying the interaction between L. johnsonii DnaK and misfolded proteins?

To study interactions between L. johnsonii DnaK and misfolded proteins, consider these methodological approaches:

• Fluorescence-based Assays:

  • Label potential substrate proteins with environment-sensitive fluorescent dyes

  • Monitor changes in fluorescence upon binding to DnaK

  • Use fluorescence anisotropy to measure binding kinetics and affinity

• Surface Plasmon Resonance (SPR):

  • Immobilize DnaK on a sensor chip

  • Flow different concentrations of substrate proteins over the surface

  • Determine association and dissociation rate constants

• Thermophoresis:

  • Microscale thermophoresis (MST) allows for measurement of interactions in solution

  • Requires minimal protein amounts and can detect a wide range of affinities

• Isothermal Titration Calorimetry (ITC):

  • Provides complete thermodynamic profile of the interaction

  • Determines binding stoichiometry, affinity, enthalpy, and entropy

• Protein Stability Assays: As demonstrated in research with the λ-repressor, the DnaK response correlates with protein stability . Design experiments with protein variants of differing stability to analyze how DnaK recognizes and responds to these differences.

• In vivo Reporter Systems: Use fluorescent reporter systems similar to those described in the literature to monitor DnaK response to expression of various misfolded proteins in real-time.

These approaches provide complementary information about the specificity, affinity, and dynamics of DnaK interactions with misfolded proteins.

How can I use L. johnsonii DnaK for strain-specific identification within Lactobacillus species?

The dnaK gene can be effectively utilized for strain-specific identification within Lactobacillus species through the following approaches:

• Multilocus Sequence Analysis (MLSA):

  • Include dnaK as one of at least 5 housekeeping genes for phylogenetic analysis

  • Combine with other recommended genes such as dnaJ, mutL, pheS, and yycH

  • Construct phylogenetic trees using concatenated sequences for higher resolution

• Single Nucleotide Polymorphism (SNP) Analysis:

  • Develop a multiplex minisequencing assay using SNP-specific primers based on dnaK gene sequences

  • This approach has demonstrated high resolution for identifying strains at the species level

• Digital DNA-DNA Hybridization (dDDH) and Average Nucleotide Identity (ANI):

  • While not specific to dnaK, these genome-based comparison methods can complement gene-specific approaches

  • Include dnaK sequence analysis as part of a comprehensive genomic assessment

• MALDI-TOF MS Analysis:

  • Develop a database that includes DnaK peptide mass fingerprints

  • Use species-specific MS peaks for identification

  • This approach allows for rapid identification at both species and subspecies levels

The research indicates that L. johnsonii strains show host-specific clustering, with strains from chickens, humans, and mice forming separate genetic clusters . Using dnaK sequences as molecular markers can help identify the origin and specificity of different L. johnsonii strains.

What role does DnaK play in L. johnsonii adaptation to different host environments?

DnaK plays a critical role in L. johnsonii adaptation to different host environments through several mechanisms:

• Host-Specific Strain Divergence: Research has shown that L. johnsonii strains cluster according to their host of origin (human, chicken, or mouse) , suggesting evolutionary adaptation. DnaK, as a stress-response protein, likely contributes to this adaptation by helping bacteria cope with host-specific stressors.

• Stress Response Mediation: Different host gastrointestinal tracts present varied stressors (pH, bile acids, antimicrobial peptides). DnaK helps L. johnsonii adapt by:

  • Preventing protein aggregation under stress conditions

  • Assisting in refolding of partially denatured proteins

  • Protecting essential cellular functions during environmental changes

• Host-Microbe Interactions: DnaK may interact with host epithelial cells or immune system components, potentially influencing:

  • Adhesion to intestinal surfaces

  • Immunomodulatory effects

  • Competitive exclusion of pathogens

• Genomic Co-evolution: The genetic variation observed among 47 L. johnsonii strains isolated from various hosts showed three distinct clusters corresponding to chickens, humans, and mice . This supports the co-evolution hypothesis, where DnaK gene variations may reflect adaptation to specific host factors.

• Metabolic Adaptation: The L. johnsonii genome shows adaptations to nutrient availability in host environments, with enhanced transport systems and unique amino acid permeases compensating for incomplete biosynthetic pathways . DnaK likely helps maintain the proteome integrity necessary for these specialized metabolic functions.

Understanding DnaK's role in host adaptation could help select appropriate L. johnsonii strains for specific probiotic applications targeted to different host species.

Can L. johnsonii DnaK be used to develop heat-stable probiotic strains for research purposes?

While using recombinant L. johnsonii DnaK to develop heat-stable probiotic strains presents a complex challenge, several research approaches show promise:

It's important to note that thermal tolerance is a complex phenotype involving multiple genes and regulatory networks. Research focusing on just DnaK should acknowledge these limitations and consider broader approaches for comprehensive heat stability engineering.

How should I design experiments to compare DnaK response to protein variants with different stabilities?

Based on the research involving DnaK response to protein variants , a robust experimental design should include:

• Protein Variant Selection:

  • Create a set of protein mutants with systematically varying thermal stabilities

  • Use a well-characterized model protein (such as λ-repressor or another protein with known stability parameters)

  • Include variants spanning a wide stability range (ΔG values)

  • Ensure mutations primarily affect stability rather than function

• Reporter System Construction:

  • Develop a fluorescent reporter system that responds to DnaK activation

  • Design constructs with inducible expression of each protein variant

  • Include controls for basal reporter expression and non-specific stress responses

• Experimental Variables to Control:

  • Protein synthesis rate (use identical promoters and ribosome binding sites)

  • Cell growth conditions (temperature, media, aeration)

  • Expression time course (measure at multiple time points)

  • Cell density (normalize measurements to OD600)

• Measurements to Collect:

  • DnaK response (reporter fluorescence)

  • Protein variant abundance (via fluorescent tag or Western blot)

  • Thermal stability of each variant (through thermal shift assays)

  • Cell-to-cell variation (using flow cytometry or single-cell microscopy)

• Data Analysis Approach:

  • Plot DnaK response against protein stability parameters

  • Analyze the correlation between stability and DnaK response at different time points

  • Separate effects of synthesis rate from accumulated protein abundance

  • Quantify cell-to-cell variability for each variant

The research indicates that initial DnaK response depends largely on protein synthesis rate, while the long-term response (as homeostasis is approached) correlates strongly with protein stability . Your experimental design should account for this temporal dimension.

What bioinformatic approaches are recommended for analyzing L. johnsonii DnaK sequence variations across different strains?

For comprehensive analysis of L. johnsonii DnaK sequence variations across different strains, implement these bioinformatic approaches:

• Multiple Sequence Alignment (MSA):

  • Align DnaK sequences using MUSCLE, MAFFT, or Clustal Omega

  • Include DnaK sequences from various L. johnsonii strains and other Lactobacillus species as references

  • Identify conserved domains and variable regions

• Phylogenetic Analysis:

  • Construct phylogenetic trees using Maximum Likelihood, Neighbor-Joining, or Bayesian methods

  • Implement bootstrap analysis (1000 replicates) to assess branch support

  • Compare DnaK-based phylogeny with whole-genome phylogeny to identify inconsistencies

• SNP Identification and Analysis:

  • Identify single nucleotide polymorphisms across aligned sequences

  • Determine if SNPs are synonymous or non-synonymous

  • Calculate dN/dS ratios to assess selective pressure on different regions of DnaK

• Structural Analysis:

  • Map sequence variations onto predicted 3D structures

  • Focus on functional domains (nucleotide-binding domain, substrate-binding domain)

  • Assess potential impacts on protein function

• Host-Specific Variation Analysis:

  • Group sequences by host origin (human, chicken, mouse)

  • Identify host-specific sequence signatures

  • Apply statistical methods to validate host-specific patterns

• Comparative Genomic Context:

  • Examine the genomic neighborhood of dnaK

  • Compare with other housekeeping genes used in MLSA (dnaJ, mutL, pheS, yycH)

  • Assess co-evolution patterns with other heat shock proteins

• Tools and Databases:

  • MEGA for alignment and phylogenetic analysis

  • PyMOL or UCSF Chimera for structural visualization

  • Pan-genome analysis tools like Roary or PGAP

  • Custom R or Python scripts for statistical analysis

This multi-faceted approach can reveal evolutionary relationships between strains and provide insights into the functional significance of observed variations in DnaK proteins.

How can I accurately measure and interpret the correlation between protein stability and DnaK response in L. johnsonii?

To accurately measure and interpret the correlation between protein stability and DnaK response in L. johnsonii, follow these methodological guidelines:

• Protein Stability Quantification:

  • Measure thermal stability (Tm) using differential scanning fluorimetry (DSF)

  • Determine thermodynamic stability (ΔG) through chemical denaturation experiments

  • Consider using circular dichroism spectroscopy for secondary structure stability

  • For each protein variant, generate complete stability profiles rather than single parameters

• DnaK Response Measurement:

  • Implement a fluorescent reporter system similar to that described in the literature

  • Use flow cytometry to capture cell-to-cell variation

  • Perform time-course experiments to distinguish between initial and steady-state responses

  • Include controls to account for non-specific stress responses

• Experimental Design Considerations:

  • Use an inducible system with titratable expression

  • Control for protein abundance through parallel quantification

  • Maintain identical growth conditions across experiments

  • Include positive controls (severely destabilized proteins) and negative controls (highly stable proteins)

• Data Analysis Framework:

  • Plot DnaK response against stability parameters using regression analysis

  • Apply multivariate analysis to account for confounding factors

  • Consider using mixed-effects models to handle cell-to-cell variability

  • Normalize data appropriately to account for differences in protein expression levels

• Interpretation Guidelines:

  • Distinguish between correlation and causation

  • Consider the biphasic response: initial response (synthesis-dependent) vs. steady-state response (stability-dependent)

  • Account for the large degree of cell-cell variation observed with more stable proteins

  • Evaluate whether the relationship is linear or follows another mathematical model

• Validation Approaches:

  • Confirm findings with multiple protein models

  • Use DnaK mutants with altered substrate binding to validate the mechanistic basis

  • Perform in vitro binding assays with purified components to corroborate in vivo findings

This comprehensive approach will provide robust data on how protein stability influences DnaK response, allowing for reliable interpretation of the underlying biological mechanisms.

What are the key considerations when using dnaK as a phylogenetic marker for Lactobacillus species identification?

When using dnaK as a phylogenetic marker for Lactobacillus species identification, researchers should consider these critical factors:

• Selection of Gene Regions:

  • Target conserved regions for primer design to ensure amplification across species

  • Include variable regions with sufficient discriminatory power

  • Consider using partial dnaK sequences that have been validated for phylogenetic analysis

• Multi-Gene Approach Requirements:

  • Always use dnaK in combination with other housekeeping genes

  • Include at least 4-5 additional genes (such as dnaJ, mutL, pheS, and yycH)

  • Perform analysis with concatenated sequences rather than individual genes

• Reference Sequence Selection:

  • Include type strains of each Lactobacillus species

  • Add multiple strains per species when available

  • Incorporate closely related species to ensure proper discrimination

• Analytical Methods:

  • Apply multiple tree-building algorithms (Maximum Likelihood, Neighbor-Joining)

  • Implement bootstrap analysis with at least 1000 replicates

  • Use appropriate evolutionary models selected through model testing

• Resolution Limitations:

  • Be aware that dnaK alone may not resolve closely related species

  • For the L. casei group, combine with mutL gene analysis for better resolution

  • Consider supplementing with whole-genome approaches for uncertain cases

• Technical Considerations:

  • Optimize PCR conditions for specificity and sensitivity

  • Sequence both DNA strands to ensure accuracy

  • Include quality control steps to detect potential contamination or paralogs

• Interpretation Guidelines:

  • No universal threshold exists for species definition using MLSA

  • Compare results with accepted taxonomic standards

  • Consider complementary approaches like ANI or dDDH for ambiguous cases

• Database Limitations:

  • Be aware that few reference sequences may be available in public databases

  • Consider contributing new sequences to improve resources for the community

  • Verify taxonomic assignments of database sequences before use

By addressing these considerations, researchers can maximize the utility of dnaK as a phylogenetic marker while avoiding potential pitfalls in Lactobacillus species identification.

What are the most common issues when working with recombinant L. johnsonii DnaK and how can they be resolved?

When working with recombinant L. johnsonii DnaK, researchers frequently encounter these challenges:

• Low Expression Yields:

  • Problem: L. johnsonii has a low GC content (34.91%) compared to E. coli, leading to codon usage issues.

  • Solution: Use codon-optimized gene synthesis, employ specialized E. coli strains containing rare tRNAs, or reduce culture temperature to 16-20°C during induction.

• Protein Aggregation/Inclusion Bodies:

  • Problem: DnaK may ironically form inclusion bodies when overexpressed.

  • Solution: Reduce induction temperature, decrease IPTG concentration, co-express with chaperones, or consider fusion tags that enhance solubility (SUMO, MBP).

• Low ATPase Activity:

  • Problem: Purified DnaK shows minimal ATPase activity.

  • Solution: Ensure ATP is present during purification, verify proper folding using circular dichroism, add magnesium (1-5 mM MgCl₂) to reaction buffers, and include co-chaperones like DnaJ to stimulate activity.

• Protein Instability:

  • Problem: DnaK degrades during purification or storage.

  • Solution: Include protease inhibitors throughout purification, avoid freeze-thaw cycles, store at -80°C in small aliquots with 10% glycerol, and consider adding ATP (0.1-1 mM) to storage buffer.

• Inconsistent Substrate Binding:

  • Problem: Variable results in substrate binding assays.

  • Solution: Carefully control nucleotide state (ATP vs. ADP), ensure proper co-chaperone ratios, pre-equilibrate DnaK with nucleotides before assays, and use freshly prepared protein.

• Contamination with E. coli DnaK:

  • Problem: Purified protein may contain E. coli DnaK contamination.

  • Solution: Confirm identity with mass spectrometry, use western blotting with antibodies specific to L. johnsonii DnaK, or employ strain-specific sequence tags for differentiation.

• Difficult Crystallization:

  • Problem: Challenges in obtaining crystals for structural studies.

  • Solution: Try crystallization with different nucleotides (ATP, ADP, AMP-PNP), remove flexible regions, or co-crystallize with substrate peptides and co-chaperones.

Each of these challenges has proven solutions based on the special properties of DnaK and the unique characteristics of L. johnsonii proteins.

How can I differentiate between specific and non-specific effects when studying DnaK interactions with target proteins?

Differentiating between specific and non-specific effects when studying DnaK interactions requires rigorous experimental controls and multiple validation approaches:

• Control Protein Selection:

  • Use structurally similar proteins with different stability profiles

  • Include proteins known not to interact with DnaK

  • Employ single-point mutants that selectively alter hydrophobic binding sites

• Competition Assays:

  • Perform competition experiments with known DnaK substrates

  • Titrate with synthetic peptides containing established DnaK binding motifs

  • Specific interactions should show competitive displacement patterns

• Nucleotide Dependence Testing:

  • Examine ATP-dependent binding and release cycles

  • Compare interactions in ATP vs. ADP states

  • Specific DnaK interactions show different affinities depending on nucleotide state

• Co-chaperone Requirements:

  • Test dependence on co-chaperones (DnaJ, GrpE)

  • True substrates show enhanced binding in the presence of DnaJ

  • Measure dissociation rates with and without GrpE

• Mutational Analysis:

  • Introduce mutations in the substrate-binding domain of DnaK

  • Create variants of target proteins with altered hydrophobic motifs

  • Systematic mapping of interaction sites through mutation can confirm specificity

• Kinetic Analysis:

  • Measure association and dissociation rates

  • Determine binding constants under different conditions

  • Specific interactions typically show defined kinetic parameters

• Binding Site Identification:

  • Use hydrogen-deuterium exchange mass spectrometry to map interaction regions

  • Perform NMR spectroscopy to identify specific binding sites

  • Cross-linking studies followed by mass spectrometry can identify contact points

• In vivo Validation:

  • Test interactions in cellular contexts

  • Use proximity ligation assays or FRET to confirm interactions

  • Compare results between in vitro and in vivo systems

By implementing multiple approaches and carefully designed controls, researchers can confidently distinguish specific DnaK-substrate interactions from non-specific binding events.

What are the most promising future research directions involving L. johnsonii DnaK?

Based on current knowledge and technological advancements, these future research directions show particular promise for L. johnsonii DnaK:

• Host-Microbe Interaction Studies:

  • Investigate DnaK's role in L. johnsonii adaptation to different host environments

  • Examine how host-specific DnaK variants influence colonization efficiency

  • Explore potential immunomodulatory effects of secreted or surface-exposed DnaK

• Structural Biology Applications:

  • Determine high-resolution structures of L. johnsonii DnaK in different nucleotide states

  • Compare with DnaK structures from pathogenic bacteria to identify unique features

  • Design small molecules that could modulate DnaK function in a species-specific manner

• Synthetic Biology Approaches:

  • Engineer L. johnsonii strains with modified DnaK to enhance stress resistance

  • Develop tunable chaperone systems for controlled protein expression

  • Create synthetic DnaK networks with novel regulatory properties

• Single-Cell Studies:

  • Investigate the cell-to-cell variation in DnaK response observed with stable proteins

  • Develop microfluidic approaches to track DnaK dynamics in individual bacteria

  • Apply stochastic modeling to understand variability in stress responses

• Comparative Genomics and Evolution:

  • Expand on studies showing host-specific clustering of L. johnsonii strains

  • Investigate co-evolution of DnaK with host factors across different host species

  • Apply molecular clock analyses to understand the timeline of diversification

• Biotechnological Applications:

  • Utilize DnaK for improving protein folding in heterologous expression systems

  • Develop DnaK-based biosensors for detecting cellular stress

  • Explore applications in protein engineering and directed evolution

• Systems Biology Integration:

  • Map the complete interactome of L. johnsonii DnaK

  • Model the dynamic behavior of the chaperone network under different stress conditions

  • Integrate transcriptomic, proteomic, and metabolomic data to understand system-level responses

These research directions leverage current technologies while addressing fundamental questions about DnaK function and its role in bacterial adaptation to diverse environments.

How might emerging technologies improve our understanding of L. johnsonii DnaK function and applications?

Emerging technologies offer transformative potential for understanding L. johnsonii DnaK function and discovering novel applications:

• Cryo-Electron Microscopy (Cryo-EM):

  • Visualize DnaK-substrate complexes in near-native conditions

  • Capture dynamic conformational changes during the chaperone cycle

  • Resolve structures of DnaK interacting with co-chaperones and substrates simultaneously

• Single-Molecule Techniques:

  • Apply single-molecule FRET to track DnaK conformational changes in real-time

  • Use optical tweezers to measure forces generated during protein folding

  • Implement super-resolution microscopy to visualize DnaK distribution in bacterial cells

• CRISPR-Based Technologies:

  • Generate precise genomic modifications in L. johnsonii dnaK gene

  • Create CRISPRi systems for controlled knockdown of DnaK expression

  • Develop CRISPR-based screening methods to identify DnaK interaction partners

• Artificial Intelligence and Machine Learning:

  • Predict DnaK substrate binding sites with improved accuracy

  • Model complex chaperone networks and predict system behaviors

  • Design optimized DnaK variants with enhanced specificity or activity

• Microfluidics and Organ-on-a-Chip:

  • Study DnaK function in simulated gut environments

  • Track bacterial adaptation to changing conditions in real-time

  • Examine host-microbe interactions in controlled microenvironments

• Synthetic Biology Tools:

  • Create genetic circuits for precise control of DnaK expression

  • Design synthetic chaperone networks with novel properties

  • Develop biosensors based on DnaK conformational changes

• Multi-Omics Integration:

  • Combine transcriptomics, proteomics, and metabolomics to understand DnaK's role in cellular homeostasis

  • Apply network analysis to identify key regulatory nodes

  • Use systems biology approaches to model chaperone dynamics

• Long-Read Sequencing:

  • Improve genomic context analysis of dnaK in different L. johnsonii strains

  • Detect structural variations that might affect DnaK function

  • Enable more accurate comparative genomics across Lactobacillus species