Recombinant Salmonella agona Cobalt transport protein CbiN (cbiN)

What is the structural composition of Recombinant Salmonella agona Cobalt transport protein CbiN?

The Cobalt transport protein CbiN from Salmonella agona (strain SL483) is a membrane protein with 93 amino acid residues. Its amino acid sequence is MKKTLMLLAMVVALVILPFFINHGGEYGGSGEAESQIQAIAPQYKPWFQPLYEPASGEI ESLLFTLQGSLGAAVIFYILGYCKGKQRRDDRA. The protein contains hydrophobic regions consistent with its transmembrane localization, which is critical for its function in cobalt transport across the cell membrane. It is recognized in UniProt under accession number B5EWY8, with the gene designated as cbiN and ordered locus name SeAg_B2144 .

What is the functional role of CbiN in Salmonella agona?

The CbiN protein functions primarily as a cobalt transport protein within Salmonella agona. It serves as a probable substrate-capture component of an energy-coupling factor (ECF) transporter system. These ECF transporters are a subset of ATP-binding cassette (ABC) transporters that facilitate the uptake of micronutrients, including transition metals such as cobalt. Specifically, CbiN is believed to capture cobalt ions from the environment and facilitate their transport across the cell membrane, a process essential for bacterial metabolism, particularly in the synthesis of vitamin B12 (cobalamin) . This functionality makes CbiN a critical component in the bacterial micronutrient acquisition systems, particularly in environments where cobalt availability may be limited.

How does one optimize storage conditions for recombinant CbiN protein?

For optimal storage of recombinant Salmonella agona CbiN protein, maintain it in a Tris-based buffer with 50% glycerol, which has been optimized specifically for this protein. Store the protein at -20°C for regular use, or at -20°C to -80°C for extended storage periods. To preserve protein integrity, avoid repeated freeze-thaw cycles as these can lead to protein denaturation and loss of functionality. For experimental work spanning up to one week, working aliquots can be maintained at 4°C . When preparing aliquots, use small volumes that will be consumed in a single experiment to minimize freeze-thaw cycles. Additionally, consider adding protease inhibitors if proteolytic degradation is a concern in your specific experimental setup.

What experimental approaches are suitable for studying CbiN function?

To study CbiN function, researchers can employ multiple complementary approaches:

• Metal binding assays: Use isothermal titration calorimetry (ITC) or fluorescence spectroscopy to quantify the binding affinity of CbiN for cobalt and other divalent cations.

• Transport assays: Implement radioactive cobalt (57Co) uptake experiments in whole cells or membrane vesicles expressing CbiN to measure transport kinetics.

• Mutagenesis studies: Apply site-directed mutagenesis to identify critical residues for metal binding and transport, followed by functional assays to assess the impact of mutations.

• Protein interaction studies: Use pull-down assays, co-immunoprecipitation, or bacterial two-hybrid systems to identify interaction partners within the ECF transporter complex.

• Structural biology approaches: Apply X-ray crystallography or cryo-electron microscopy to determine the three-dimensional structure of CbiN alone or in complex with its ECF transporter partners .

Selection of appropriate experimental design methods, such as factorial designs or response surface methodologies, can help optimize these approaches and maximize information yield while minimizing resource expenditure .

How should researchers design experiments to investigate the relationship between CbiN expression and S. agona virulence?

Investigating the relationship between CbiN expression and S. agona virulence requires a multifaceted experimental approach:

Table 1: Experimental Design for CbiN-Virulence Relationship Studies

Implement a central composite design (CCD) to systematically explore the interaction effects between cobalt availability, pH, oxygen tension, and temperature on CbiN expression and virulence. This approach allows for the identification of optimal conditions and potential interaction effects between variables. Consider using S. agona strains isolated from clinical outbreaks, such as those associated with gastrointestinal disease outbreaks in Australia, as these may exhibit enhanced virulence properties . To correlate CbiN activity with Salmonella pathogenicity, examine the expression of CbiN in the context of Salmonella pathogenicity islands (SPIs) activation, particularly SPI-1 and SPI-2, which are crucial for host cell invasion and intracellular survival .

What methodologies are recommended for studying the role of CbiN in antibiotic resistance mechanisms in S. agona?

To investigate CbiN's potential role in antibiotic resistance mechanisms in S. agona, researchers should implement a comprehensive methodological framework:

• Transcriptional coupling analysis: Utilize RT-qPCR to determine whether cbiN expression correlates with expression of antibiotic resistance genes under various antibiotic stresses. Compare expression patterns between susceptible and resistant S. agona isolates, particularly focusing on those carrying IncHI2 plasmids known to harbor multiple antimicrobial resistance genes .

• Genetic proximity assessment: Analyze the genomic context of cbiN in relation to antibiotic resistance genes, particularly in strains carrying large plasmids like pSE18-SA00377-1, which contains 16 different antibiotic resistance genes organized in clusters . Map potential operonic structures and regulatory elements that might co-regulate cbiN with resistance determinants.

• Metal-antibiotic interaction studies: Design experiments using a Box-Behnken or Plackett-Burman design to evaluate potential synergistic or antagonistic interactions between cobalt transport (mediated by CbiN) and antibiotic efficacy across various antibiotic classes . This is particularly relevant since metal homeostasis can affect antibiotic susceptibility.

• CRISPR-Cas9 modulation: Implement targeted gene editing to overexpress or knock out cbiN, then determine minimum inhibitory concentrations (MICs) for various antibiotics. Compare with wild-type strains and complement mutants to establish causative relationships.

• Biofilm formation analysis: Assess whether CbiN expression influences biofilm formation capacity, which can contribute to antibiotic tolerance. Use crystal violet staining, confocal microscopy, and biomass quantification to measure biofilm characteristics under varying cobalt concentrations.

The experimental design should incorporate multi-factorial approaches to account for potential interactions between cobalt transport, membrane permeability, and drug efflux systems. Given that S. agona isolates have been found to carry plasmids with extensive antimicrobial resistance determinants, special attention should be paid to plasmid-mediated resistance mechanisms and how CbiN might interact with these systems .

How can researchers effectively characterize the interaction between CbiN and other components of the ECF transporter complex?

Characterizing the interactions between CbiN and other components of the ECF transporter complex requires multiple complementary approaches:

• Co-immunoprecipitation coupled with mass spectrometry: Use antibodies against CbiN to pull down interaction partners, followed by mass spectrometric identification. This approach can identify both stable and transient interactions within the native complex.

• Bacterial two-hybrid (B2H) or split-protein complementation assays: These systems allow for in vivo detection of protein-protein interactions by linking protein interactions to a measurable output signal (e.g., antibiotic resistance or enzyme activity).

• Surface plasmon resonance (SPR) or biolayer interferometry (BLI): These techniques provide real-time, label-free measurements of binding kinetics between purified CbiN and other ECF components, allowing determination of association/dissociation rates and binding affinities.

• Cryo-electron microscopy: This structural biology approach can visualize the entire ECF complex, including CbiN's position and interactions within the complex architecture.

• Crosslinking mass spectrometry (XL-MS): Chemical crosslinkers can capture transient interactions, and subsequent mass spectrometry can identify crosslinked peptides, providing distance constraints for modeling protein complexes.

The experimental design should follow a fractional factorial approach to efficiently test multiple conditions and interaction partners . Given that CbiN functions as an S-component in ECF transporters, focus particularly on interactions with the T-component (transmembrane energy-coupling module) and the A-components (ATPases that power substrate transport). Researchers should also consider investigating potential conformational changes in CbiN upon substrate binding or during the transport cycle, which can be assessed using hydrogen-deuterium exchange mass spectrometry or single-molecule FRET techniques.

What genomic analysis approaches would be most informative for studying CbiN evolution across Salmonella serovars?

To conduct comprehensive evolutionary analyses of CbiN across Salmonella serovars, researchers should implement the following genomic approaches:

• Comparative sequence analysis: Perform multiple sequence alignments of cbiN genes and their encoded proteins across diverse Salmonella serovars, identifying conserved regions that likely represent functionally critical domains and variable regions that may relate to serovar-specific adaptations.

• Phylogenetic reconstruction: Construct maximum likelihood or Bayesian phylogenetic trees based on cbiN sequences, comparing these with whole-genome-based phylogenies to identify potential horizontal gene transfer events or unusual evolutionary patterns.

• Selection pressure analysis: Calculate dN/dS ratios (non-synonymous to synonymous substitution rates) across cbiN codons to identify positions under positive or purifying selection, which can provide insights into functional constraints and adaptive evolution.

• Genomic context analysis: Examine the conservation of gene neighborhoods surrounding cbiN across serovars, focusing on operonic structures and potential regulatory elements that may co-evolve with cbiN.

• Recombination detection: Apply methods such as GARD (Genetic Algorithm for Recombination Detection) to identify potential recombination breakpoints in cbiN sequences, which could indicate mosaic evolutionary history.

What experimental design would best elucidate the role of CbiN in S. agona survival under cobalt-limited conditions?

To investigate CbiN's role in S. agona survival under cobalt-limited conditions, I recommend implementing a central composite design (CCD) that systematically explores multiple variables affecting cobalt availability and bacterial response:

Table 2: Central Composite Design for Studying CbiN Function Under Cobalt Limitation

This design would include:

• Comparative growth studies: Compare wild-type S. agona with ΔcbiN mutants across various cobalt concentrations, monitoring growth rates, lag phases, and maximum cell densities.

• Competition assays: Co-culture wild-type and ΔcbiN mutants under cobalt limitation, using strain-specific markers to track population dynamics over time.

• Transcriptome analysis: Perform RNA-Seq to identify compensatory mechanisms activated in response to cbiN deletion under cobalt-limited conditions.

• Metabolomic profiling: Quantify intracellular cobalt levels, vitamin B12 derivatives, and metabolites in related pathways to assess the metabolic consequences of CbiN deficiency.

• Host cell invasion assays: Determine whether cobalt limitation and CbiN function affect virulence properties by measuring invasion efficiency in epithelial cell models.

The central composite design would allow for the modeling of response surfaces and identification of potential interaction effects between variables . For instance, pH may influence cobalt solubility and availability, while temperature may affect membrane fluidity and transporter function. This approach would provide a comprehensive understanding of CbiN's role in cobalt acquisition and its importance for S. agona survival under environmentally relevant conditions.

How can researchers investigate the potential relationship between CbiN function and heavy metal resistance mechanisms in S. agona?

To investigate the relationship between CbiN function and heavy metal resistance in S. agona, researchers should implement a multifaceted approach that addresses both physiological responses and molecular mechanisms:

Consider implementing a fractional factorial design to efficiently explore the interaction effects between multiple variables, including metal type, concentration, exposure time, pH, and growth phase . This approach would be particularly valuable given the complex interplay between different metal homeostasis systems in bacteria and the potential for cross-resistance or cross-sensitivity effects.

What are the optimal purification strategies for recombinant CbiN to maintain its native conformation?

For optimal purification of recombinant CbiN while preserving its native conformation, researchers should consider the following methodological approach:

• Expression system selection: Choose an expression system that supports proper membrane protein folding and insertion. E. coli C41(DE3) or C43(DE3) strains, which are derivatives of BL21(DE3) optimized for membrane protein expression, are recommended. Alternatively, consider cell-free expression systems supplemented with lipid nanodiscs or detergent micelles.

• Detergent screening: Since CbiN is a membrane protein, systematic screening of detergents is crucial. Test a panel including mild detergents (e.g., n-dodecyl-β-D-maltoside, digitonin), harsh detergents (e.g., sodium dodecyl sulfate), and novel amphipathic polymers (e.g., styrene-maleic acid copolymers) to identify conditions that effectively solubilize CbiN while maintaining its structure.

• Affinity tag selection: For initial capture, consider a dual tagging strategy with a polyhistidine tag for IMAC (immobilized metal affinity chromatography) purification and a secondary tag (e.g., Strep-tag II) for additional purification. Place tags at positions least likely to interfere with protein folding, ideally at the N-terminus or C-terminus based on topology predictions.

• Sequential chromatography: Implement a multi-step purification process:

  • IMAC using cobalt or nickel resins (adjusting for potential binding competition with the protein's native cobalt-binding activity)

  • Ion exchange chromatography (IEX) based on CbiN's predicted isoelectric point

  • Size exclusion chromatography (SEC) as a final polishing step and to assess oligomeric state

• Conformational validation: After purification, verify protein conformation using circular dichroism (CD) spectroscopy to assess secondary structure content, tryptophan fluorescence to monitor tertiary structure, and thermal shift assays to evaluate stability under different buffer conditions.

Researchers should implement a Box-Behnken design to optimize key variables such as detergent type/concentration, salt concentration, pH, and temperature during purification . This approach allows efficient exploration of the parameter space while minimizing the number of experiments needed. Additionally, consider incorporating cobalt ions in the purification buffers if binding studies suggest they stabilize CbiN's native conformation.

How can researchers quantitatively assess CbiN-mediated cobalt transport in bacterial systems?

To quantitatively assess CbiN-mediated cobalt transport in bacterial systems, researchers should implement a comprehensive toolkit of complementary approaches:

• Radioisotope uptake assays: Use radioactive ⁵⁷Co to directly measure transport kinetics. Compare uptake rates between wild-type strains, cbiN deletion mutants, and complemented strains under various conditions. Time-course measurements can provide information on initial rates and saturation.

• ICP-MS quantification: Employ inductively coupled plasma mass spectrometry (ICP-MS) to precisely measure intracellular cobalt concentrations. This non-radioactive approach allows for simultaneous quantification of multiple metals to detect potential competition effects.

• Fluorescent metal sensors: Develop or utilize genetically encoded fluorescent sensors that respond to intracellular cobalt levels. These systems can enable real-time, single-cell monitoring of cobalt influx and cellular distribution.

• Membrane vesicle transport assays: Prepare inside-out or right-side-out membrane vesicles from bacteria expressing CbiN and measure ATP-dependent or ion gradient-driven cobalt transport in a controlled in vitro system.

• Electrophysiological approaches: For detailed mechanistic studies, consider reconstituting CbiN in planar lipid bilayers or using patch-clamp techniques on giant bacterial spheroplasts to measure transport-associated currents and characterize the transport mechanism.

The experimental design should follow a response surface methodology, particularly a central composite design, to optimize key parameters such as external cobalt concentration, pH, temperature, and competing ion concentrations . This approach would allow researchers to model the transport kinetics and identify optimal conditions for CbiN activity.

For data analysis, fit transport data to appropriate kinetic models (e.g., Michaelis-Menten for saturable transport) to determine parameters such as Km (apparent affinity), Vmax (maximum transport rate), and potential Hill coefficients if cooperative binding is suspected. Compare these parameters across different experimental conditions and genetic backgrounds to develop a comprehensive model of CbiN-mediated cobalt transport.

What bioinformatic approaches can reveal the evolutionary history of CbiN across bacterial species?

To elucidate the evolutionary history of CbiN across bacterial species, researchers should implement a comprehensive bioinformatic workflow that integrates multiple analytical approaches:

• Homology detection and sequence retrieval: Use PSI-BLAST and HMMer searches against comprehensive databases (e.g., NCBI nr, UniProt) to identify CbiN homologs across diverse bacterial phyla. Employ profile-based methods to detect remote homologs that might be missed by conventional BLAST searches.

• Phylogenetic analysis: Construct maximum likelihood and Bayesian phylogenetic trees using appropriate evolutionary models selected through model testing (e.g., ProtTest). Compare gene trees with species trees to identify potential horizontal gene transfer events, which are particularly important given the observation that CbiN-encoding genes may be carried on mobile genetic elements .

• Synteny analysis: Examine the genomic context of cbiN across species to identify conserved gene neighborhoods and operonic structures. This can provide insights into functional associations and co-evolutionary patterns with other cobalt transport or vitamin B12 biosynthesis components.

• Selection pressure analysis: Apply codon-based methods (e.g., PAML, HyPhy) to calculate dN/dS ratios across the alignment and identify sites under positive, negative, or relaxed selection. This can highlight functionally important residues and adaptive evolutionary patterns.

• Ancestral sequence reconstruction: Infer the sequences of ancestral CbiN proteins at key nodes in the phylogeny using maximum likelihood or Bayesian approaches. This can provide insights into the functional evolution of the protein.

• Domain architecture analysis: Examine the presence of additional domains or motifs in CbiN across different species, which might indicate functional diversification or specialization.

• Coevolutionary analysis: Identify potential coevolving residues within CbiN using methods such as mutual information analysis or direct coupling analysis. These patterns can reveal functional or structural constraints.

This comprehensive analysis would be particularly informative given the findings that S. agona strains like SG17-135 are part of globally disseminated clonal lineages , and that resistance determinants can be shared across diverse bacterial genera through plasmid transfer . Understanding the evolutionary history of CbiN could provide insights into adaptation strategies and the potential for gene transfer between pathogens.

How should researchers approach the study of CbiN's role in the context of Salmonella pathogenicity islands?

To investigate CbiN's role in the context of Salmonella pathogenicity islands (SPIs), researchers should implement a structured, multi-level research approach:

• Computational co-expression analysis: Analyze existing transcriptomic datasets to identify potential co-expression patterns between cbiN and known SPI genes. Use weighted gene co-expression network analysis (WGCNA) to identify gene modules that include both cbiN and virulence factors.

• Conditional expression studies: Design experiments to measure cbiN expression under conditions known to induce SPI expression (e.g., low pH, low oxygen, high osmolarity) using RT-qPCR or transcriptome analysis. Compare with expression profiles of key SPI genes involved in type III secretion systems (from SPI-1, SPI-2) and type I secretion systems (from SPI-4, SPI-9) .

• Genetic interaction studies: Create single and double mutants in cbiN and key SPI genes, then assess phenotypes related to virulence (invasion, intracellular survival) to identify potential genetic interactions. Implement a fractional factorial design to efficiently explore multiple gene combinations .

• Cobalt dependency of SPI function: Investigate whether SPI-encoded secretion systems require cobalt as a cofactor or structural component, and whether CbiN-mediated cobalt transport affects their assembly or function. Use varying cobalt concentrations and chelators to manipulate cobalt availability.

• In vivo infection models: Compare the virulence of wild-type and ΔcbiN mutants in animal models, focusing on colonization of specific tissues and expression of SPI genes during infection. Use a qualitative phenomenological approach to understand the lived experience of infection with different bacterial strains .

• Structural biology approaches: If direct protein-protein interactions are suspected between CbiN and SPI components, use techniques such as bacterial two-hybrid screens, co-immunoprecipitation, or crosslinking mass spectrometry to identify and characterize these interactions.

This research would be particularly relevant given that S. agona strains like SG17-135 carry extensive virulence gene cargo, including multiple Salmonella pathogenicity islands (SPIs 1, 2, 3, 4, 5, 8, and 9) . Understanding how cobalt transport systems like CbiN interact with these virulence determinants could provide insights into the mechanisms of S. agona pathogenicity and potentially identify new targets for intervention.