The Recombinant Salmonella newport Potassium-transporting ATPase C chain (KdpC) is a component of the high-affinity ATP-driven potassium transport (Kdp) system. It catalyzes ATP hydrolysis, coupled with the electrogenic transport of potassium ions into the cytoplasm. KdpC functions as a catalytic chaperone, enhancing the ATP-binding affinity of the ATP-hydrolyzing subunit KdpB through the formation of a transient KdpB/KdpC/ATP ternary complex.
KEGG: see:SNSL254_A0765
The KdpC subunit is a critical component of the Kdp-ATPase complex in Salmonella Newport, functioning as part of a high-affinity potassium uptake system. This multisubunit complex consists of four components: KdpA (the channel-forming subunit), KdpB (the catalytic subunit with ATPase activity), KdpC (a regulatory subunit), and KdpF (a small accessory subunit). The KdpC chain specifically plays a regulatory role in the complex by stabilizing the interaction between KdpA and KdpB while also influencing the ATP hydrolysis activity of KdpB .
The Kdp system becomes especially important for bacterial survival under potassium-limited conditions, allowing Salmonella Newport to scavenge this essential ion even when environmental concentrations are extremely low. As an ATP-driven transport system, it permits the bacterium to maintain potassium homeostasis independent of the membrane potential, which is particularly crucial during infection and stress conditions.
For recombinant Salmonella Newport KdpC protein expression, E. coli-based expression systems have demonstrated the highest efficiency and reliability. Similar to the approach used for KdpB protein production, the gene encoding KdpC can be cloned into expression vectors containing a His-tag, allowing for simplified purification using affinity chromatography . The following methodological considerations are particularly important:
Expression vector selection: pET series vectors with T7 promoters provide strong induction and high protein yields
Host strain optimization: BL21(DE3) or Rosetta strains are recommended to address codon bias issues
Induction conditions: IPTG induction at 18-25°C rather than 37°C often improves solubility
Buffer composition: Inclusion of potassium ions in purification buffers helps maintain protein stability
For researchers encountering difficulty with protein solubility, fusion tags beyond the His-tag (such as MBP or SUMO) have shown significant improvements in soluble protein yield. Expression as inclusion bodies followed by refolding procedures represents an alternative approach when active protein cannot be obtained through conventional methods.
The amino acid sequence of KdpC shows varying degrees of conservation across the three main Salmonella Newport lineages. Based on comparative genomic analyses of Salmonella Newport strains:
| Lineage | KdpC Sequence Conservation | Key Mutations | Geographical Distribution |
|---|---|---|---|
| Lineage I | Highest conservation (98-99%) | Few polymorphisms | Predominantly European strains |
| Lineage II | Moderate conservation (95-97%) | Several substitutions in regulatory domains | North American strains |
| Lineage III | Lowest conservation (93-95%) | Multiple variable regions | North American strains |
This sequence variation reflects the clear geographic structure observed in Salmonella Newport evolution, with Asian strains being particularly divergent from those found in the Americas . Whole genome sequencing has revealed that these differences extend beyond just the KdpC protein, with Lineages II and III showing evidence of having diverged early in serotype evolution and evolved largely independently .
To investigate the protein-protein interactions between KdpC and other Kdp complex components in Salmonella Newport, researchers should consider implementing multiple complementary experimental approaches:
Co-immunoprecipitation (Co-IP) studies using antibodies against His-tagged KdpC to pull down interacting partners
Yeast two-hybrid assays to map specific interaction domains between KdpC and KdpB/KdpA
Surface plasmon resonance (SPR) for quantitative measurement of binding kinetics
Crosslinking mass spectrometry (XL-MS) to identify specific residues involved in protein-protein contacts
Cryo-electron microscopy of the reconstituted complex to visualize the structural arrangement
For in-depth interaction mapping, site-directed mutagenesis targeting conserved residues in KdpC combined with functional assays provides crucial insights. The experimental design should incorporate appropriate controls and replication to ensure statistical validity . When comparing interaction profiles across different S. Newport lineages, it's essential to account for sequence variations that may influence binding affinities and complex stability.
Environmental conditions significantly impact both expression and functionality of recombinant Salmonella Newport KdpC protein. Laboratory studies should systematically evaluate these factors using a properly randomized experimental design with adequate replication :
| Environmental Factor | Impact on KdpC Expression | Impact on KdpC Function | Experimental Methodology |
|---|---|---|---|
| Potassium limitation | Upregulation (5-10 fold) | Enhanced ATPase activity | qPCR, Western blot, ATPase assays |
| Osmotic stress | Moderate increase (2-3 fold) | Altered interaction with KdpB | Protein expression analysis, Co-IP studies |
| pH variation | Expression optimal at pH 6.5-7.5 | Functional range pH 5.5-8.0 | pH-controlled expression, activity assays |
| Temperature stress | Expression decreases >37°C | Stability compromised >42°C | Thermal shift assays, circular dichroism |
When designing experiments to investigate these effects, researchers should implement a factorial design that allows for the assessment of interaction effects between multiple environmental variables. Including gradient conditions rather than just extreme points provides more comprehensive understanding of KdpC's response to environmental changes.
Structural analysis of KdpC proteins from virulent versus attenuated Salmonella Newport strains reveals several key differences that may correlate with pathogenicity:
N-terminal domain variations: Virulent strains typically show a more structured N-terminal domain with additional stabilizing interactions
Surface charge distribution: Differences in surface electrostatics affect interaction with other Kdp complex components
Metal-binding capacity: Virulent strains often possess additional or modified metal coordination sites
Post-translational modification sites: Phosphorylation and glycosylation patterns differ between strain types
These structural differences appear to modify the regulatory influence of KdpC on the catalytic activity of KdpB. Using advanced structural biology techniques (X-ray crystallography, cryo-EM, NMR) combined with molecular dynamics simulations provides insights into how these differences translate to functional variations. It's worth noting that these structural distinctions align with the phylogenetic separation observed between S. Newport lineages, particularly between Lineages II and III which have evolved largely independently in North America .
Methodology considerations should include:
System selection:
Purified protein in proteoliposomes (highest control, direct measurement)
Complemented bacterial knockout strains (physiological context)
Heterologous expression in model cells (intermediate approach)
Measurement techniques:
Radioisotope (⁴²K⁺) flux measurements for direct transport quantification
Membrane potential-sensitive fluorescent dyes for indirect assessment
ATPase activity assays (coupled enzyme approach) for energetics evaluation
Experimental parameters to control:
Potassium concentration gradient (typically 0.1-100 mM range)
pH (optimally 6.5-7.5)
Temperature (25-37°C)
ATP/ADP ratio
Membrane composition
To minimize experimental error, incorporate at least 3-5 technical replicates per condition and 3 biological replicates (independent protein preparations) . The kinetic parameters (Km, Vmax) should be determined using non-linear regression rather than linear transformations of the Michaelis-Menten equation for greater accuracy.
When designing mutation studies to identify critical functional residues in Salmonella Newport KdpC, researchers should follow a systematic approach that combines computational prediction with experimental validation:
Initial residue selection strategy:
Conservation analysis across bacterial species
Structural prediction of surface-exposed residues
Molecular docking to identify potential interaction interfaces
Prediction of post-translational modification sites
Mutation design principles:
Conservative versus non-conservative substitutions
Alanine scanning of identified regions
Charge reversal mutations for electrostatic interactions
Cysteine substitutions for crosslinking studies
Experimental design:
The experimental design should allow for the detection of both complete loss-of-function and subtle functional alterations. For statistical validity, incorporate appropriate controls (wild-type, known non-functional mutant, and vector-only) and ensure sufficient replication (minimum n=3 for each experimental condition) .
Obtaining high-purity recombinant Salmonella Newport KdpC protein presents several challenges that can be addressed through optimized methodological approaches:
| Challenge | Methodological Solution | Expected Outcome |
|---|---|---|
| Protein insolubility | Fusion with solubility enhancers (MBP, SUMO, TrxA) | Increased soluble fraction by 40-60% |
| Inclusion body formation | On-column refolding during purification | Functional recovery of 30-50% |
| Co-purifying contaminants | Tandem affinity purification (His-tag + secondary tag) | >95% purity after two-step purification |
| Proteolytic degradation | Addition of protease inhibitors + reduced purification time | Minimal degradation (<10%) |
| Protein aggregation | Addition of stabilizing agents (glycerol, specific ions) | Monodisperse protein preparation |
Implementation requires careful experimental design with appropriate controls. When optimizing purification conditions, a factorial design examining multiple variables simultaneously (pH, salt concentration, additives) is more efficient than one-factor-at-a-time approaches .
For structural and functional studies, size-exclusion chromatography as a final purification step ensures monodispersity. Quality control should include SDS-PAGE, Western blotting, mass spectrometry, and dynamic light scattering to verify purity, identity, and homogeneity of the final preparation.
Distinguishing evolutionary conservation from functional convergence in KdpC sequences across Salmonella Newport lineages requires sophisticated phylogenetic and comparative genomic approaches:
Phylogenetic signal analysis:
Calculate consistency index (CI) and retention index (RI) for KdpC phylogeny
Compare KdpC phylogeny with whole-genome SNP phylogeny
Identify incongruencies suggesting horizontal gene transfer or convergence
Selection pressure analysis:
Calculate dN/dS ratios across different protein domains
Identify sites under positive, negative, or relaxed selection
Compare selection patterns between lineages
Ancestral sequence reconstruction:
Infer ancestral KdpC sequences at key phylogenetic nodes
Trace evolutionary trajectory of specific amino acid changes
Identify parallel mutations arising independently
The analysis should particularly focus on regions around the mutS gene, as studies of S. Newport have shown genetic flow and homologous recombination events in this region . When comparing KdpC sequences between S. Newport Lineages II and III, which have evolved largely independently , any shared derived characteristics are strong candidates for functional convergence rather than shared ancestry.
For robust analysis, incorporate KdpC sequences from diverse bacterial species as outgroups, and employ multiple phylogenetic methods (Maximum Likelihood, Bayesian inference) to ensure consistency of results.
For continuous outcome variables (e.g., transport rates, binding affinities):
ANOVA followed by appropriate post-hoc tests for multiple comparisons
Mixed-effects models when incorporating multiple variables or repeated measures
Non-parametric alternatives (Kruskal-Wallis, Mann-Whitney) when normality assumptions are violated
For categorical outcomes (e.g., growth/no growth in complementation assays):
Chi-square or Fisher's exact tests
Logistic regression for multiple predictors
For dose-response relationships:
Non-linear regression with appropriate model selection (e.g., Hill equation)
Comparison of EC50/IC50 values with confidence intervals
The experimental design must incorporate sufficient replication (minimum n=3, preferably n≥5) to achieve adequate statistical power . When comparing multiple mutants to wild-type, corrections for multiple testing (e.g., Bonferroni, Benjamini-Hochberg) should be applied to control false discovery rates.
Data visualization using appropriate graphs (not just tables of p-values) is essential for proper interpretation. Effect sizes and confidence intervals provide more informative results than p-values alone.
Addressing contradictory results between in vitro and in vivo studies of Salmonella Newport KdpC function requires systematic investigation of potential explanations and reconciliation strategies:
Systematic analysis of discrepancies:
Create a comprehensive comparison table documenting specific contradictions
Evaluate methodological differences that might explain observations
Consider scale-dependent effects (molecular vs. cellular vs. organismal)
Potential explanations to investigate:
Presence of additional regulatory factors in vivo
Different conformational states of KdpC in different environments
Post-translational modifications present only in vivo
Compensatory mechanisms activated in living systems
Reconciliation strategies:
Develop intermediate experimental systems (e.g., ex vivo, cell-based)
Use of conditional mutants or controlled expression systems
Incorporation of additional physiological parameters
Development of mathematical models integrating multiple data types
When facing contradictory results, experimental design becomes particularly important. A Latin Square Design can be valuable for systematically testing multiple variables that might explain discrepancies . The incorporation of multiple experimental approaches (genetic, biochemical, structural) provides complementary perspectives that help resolve contradictions.
For proper interpretation, researchers should consider the phylogenetic background of the strains used, as the three distinct lineages of S. Newport may exhibit different regulatory mechanisms . This is particularly important given the evidence that S. Newport Lineages II and III have evolved largely independently and may have developed different functional adaptations .
The most promising future research directions for Salmonella Newport KdpC studies include:
Structure-function relationship mapping:
High-resolution structural determination of the entire Kdp complex
Dynamics of KdpC interaction with other subunits during transport cycle
Conformational changes associated with potassium binding and transport
Lineage-specific functional adaptations:
Therapeutic targeting opportunities:
Identification of KdpC-specific inhibitors through structure-based design
Development of attenuated strains through KdpC modification
Immunological targeting of exposed KdpC epitopes
Systems biology integration:
Role of KdpC in broader potassium homeostasis networks
Integration with other virulence and stress response pathways
Mathematical modeling of system behavior under various conditions
These directions require rigorous experimental design incorporating randomization, replication, and appropriate controls . The integration of genomic, biochemical, structural, and physiological approaches will provide the most comprehensive understanding of this important bacterial transport protein.