Multimodal cadmium resistance and its regulatory networking in Pseudomonas aeruginosa strain CD3

Abstract

Cadmium, a toxic heavy metal, poses significant global concern. A strain of the genus Pseudomonas, CD3, demonstrating significant cadmium resistance (up to 3 mM CdCl₂.H₂O) was identified from a pool of 26 cadmium-resistant bacteria isolated from cadmium-contaminated soil samples from Malda, India. The minimum inhibitory concentrations (MICs) for cadmium and other heavy metals/metalloids were determined with clarity using a modified chemically-defined medium inoculated with variable inoculum density. Formation of biofilm enabled CD3 cells to resist up to 0.75 mM CdCl₂.H₂O. Survival and growth of CD3 cells in presence of > 1 mM CdCl₂.H₂O was dependent on efflux mechanism. Efflux mechanism in CD3 was confirmed by atomic absorption spectroscopy. Resistance to cadmium was inducible when grown in presence of ≥ 1.0 mM CdCl₂.H₂O. Minimum concentration of cadmium or zinc or cobalt salts required for induction of cadmium resistance was determined. Whole-genome-based phylogenetic tools identified CD3 as the closest relative to Pseudomonas aeruginosa DSM50071^T. Bioinformatic analyses revealed a complex network of regulations, with BfmR playing a crucial role in the functions of CzcR and CzcS, essential for biofilm formation and receptor signalling pathways. Comparative genomics and mutation landscape analyses of cadmium-resistance genes in P. aeruginosa strains revealed dynamism in evolution of cadmium resistance.

Keywords: Pseudomonas aeruginosa; Biofilm; CD3; Cadmium; CzcCBA; Induction.

Fig. 1

(a) Growth responses of CD3 in liquid MSM supplemented with a graded elevation of CdCl₂.H₂O concentration; (b) Potential inducibility of cadmium resistance in CD3 through preexposure in different concentrations of CdCl₂.H₂O.

Fig. 2

Differential accumulation of cadmium in supernatant, cell-bound, and intracellular compartments of living and heat-killed CD3 cells. The difference between cell bound Cd²⁺ of living cells and heat killed cells of CD3 is statistically very significant (**P = 0.0015).

Fig. 3

(a) Comparative growth curves of CD3 in liquid MSM in response to varying pH and supplementation of 1 mM CdCl₂.H₂O; (b) Spectrophotometric quantification of biofilm formation by strain CD3 in response to varying concentrations of CdCl₂.H₂O. Statistically very significant differences (denoted by **) were observed between 0 mM and 0.75 mM (**P = 0.0063), 0 mM and 1 mM (**P = 0.014), and 0 mM and 1.5 mM (** P = 0.0042). Significant differences (denoted by *) were noted between 0 mM and 0.5 mM (*P = 0.0306) and between 0.75 mM and 1.5 mM (*P = 0.0480).

Fig. 4

Whole-genome-based phylogenetic tree of P. aeruginosa strain CD3 prepared in TYGS server.

Fig. 5

Single-nucleotide-polymorphism (SNP)-based phylogenetic tree of strain CD3 with other members of P. aeruginosa species.

Fig. 6

(a) Molecular phylogeny of Pseudomonas aeruginosa strain CD3 on the basis of concatenated nucleotide sequences of czcC, czcB, and czcA (Evolutionary analysis by Maximum Likelihood method: The evolutionary history was inferred by using the Maximum Likelihood method and Kimura 2-parameter model. The tree with the highest log likelihood (-54347.14) is shown. The percentage of trees in which the associated taxa clustered together is shown next to the branches. Initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the Maximum Composite Likelihood (MCL) approach and then selecting the topology with superior log likelihood value. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. This analysis involved 16 nucleotide sequences. Codon positions included were 1st + 2nd + 3rd + Noncoding. There was a total of 6109 positions in the final dataset. Evolutionary analyses were conducted in MEGA11); (b) Molecular phylogeny of Pseudomonas aeruginosa strain CD3 on the basis of concatenated protein sequences of czcC, czcB, and czcA (Evolutionary analysis by Maximum Likelihood method: The evolutionary history was inferred by using the Maximum Likelihood method and JTT matrix-based model. The tree with the highest log likelihood (-27689.44) is shown. The percentage of trees in which the associated taxa clustered together is shown next to the branches. Initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the JTT model, and then selecting the topology with superior log likelihood value. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. This analysis involved 16 amino acid sequences. There were a total of 2060 positions in the final dataset. Evolutionary analyses were conducted in MEGA11).

Fig. 7

Analysis of dominant (non-synonymous) point mutations in cadmium-resistance-related gene loci of the CD3 genome as compared to Pseudomonas aeruginosa strains PA01, MR41 (JCM5962), and San_ai (NCAIM B.001380).

Fig. 8

Protein–protein interaction network constructed using STRING v12 using BfmR, CzcR and CzcC as multiple “protein query sequence” queries with Pseudomonas aeruginosa PA01 (NCBI taxonomy ID: 208964) as model organism. Network nodes represent proteins, splice isoforms, or post-translational modifications are collapsed, i.e., each node represents all the proteins produced by a single, protein-coding gene locus; Edges: Edges represent specific and meaningful protein–protein associations, i.e., proteins jointly contribute to a shared function.

Fig. 9

Network interpretation and functional enrichment analysis of BfmR, BfmS, CzcR, and CzcS proteins to explore their multifaced roles and database-determined, shared activities in Pseudomonas aeruginosa biology in relation to regulation of biofilm formation, phosphorelay sensor-kinase activity and receptor signaling activity employing ClueGo (v2.5.10) and CluePedia (v1.5.10) plug-ins in the open-source software platform Cytoscape (v3.10.1).

Fig. 10

A hypothesized model of the molecular mechanism of cadmium resistance in strain CD3. A. Scenario under low cadmium stress condition, where BfmR is bound near the CzcCBA promoter region inhibiting CzcR promoter binding, Czc pump is inactive and cell is protecting itself against cadmium stress solely through vigorous biofilm formation; B. Scenario under high cadmium stress condition: 1. Adsorption of cadmium ions at the cell surface and diffusion of cadmium ions inside the cell, 2. Change in the cell wall integrity/net charge collectively sends stimulus (in a yet unknown mechanism) to BfmS and it gets autophosphorylated; CadR binds to 4 cadmium ions and activates CadA, 3. Phosphorylated BfmS phosphorylates BfmR, which has a lower binding affinity towards DNA; activated CadA effectively transfers cadmium ions into periplasmic space along with CzcD, a cation-diffusion-family protein serving the same purpose, 4. Phosphorylated BfmR gets detached from DNA. This event indicates a decrease in biofilm development, which reallocates cellular resources towards the activation of the Czc efflux mechanism; periplasmic cadmium ions bind to CzcS, 5. CzcS gets autophosphorylated upon binding to cadmium ions. 6. Phosphorylated CzcS phosphorylates CzcR protein, 7. Phosphorylated CzcR, binds to the CzcCBA promoter region in the absence of BfmR. The detachment of BfmR and the subsequent binding of CzcR is crucial for the functioning of the CzcCBA efflux pump, which aids in the process of detoxification, as previously anticipated. 8. Active transcription of CzcCBA operon under the operational control of CzcR and activation of CzcCBA pump, 9. Active efflux of cadmium ions through the CzcCBA pump.