The Copper Resistome of Group B Streptococcus Reveals Insight into the Genetic Basis of Cellular Survival during Metal Ion Stress

ABSTRACT

In bacteria, copper (Cu) can support metabolic processes as an enzymatic cofactor but can also cause cell damage if present in excess, leading to intoxication. In group B Streptococcus (GBS), a system for control of Cu efflux based on the prototypical cop operon supports survival during Cu stress. In some other bacteria, genetic systems additional to the cop operon are engaged during Cu stress and also contribute to the management of cellular Cu homeostasis. Here, we examined genetic systems beyond the cop operon in GBS for regions that contribute to survival of GBS in Cu stress using a forward genetic screen and probe of the entire bacterial genome. A high-density mutant library, generated using pGh9-ISS1, was used to expose GBS to Cu stress and compare it to nonexposed controls en masse. Eight genes were identified as essential for GBS survival in Cu stress, whereas five genes constrained GBS growth in Cu stress. The genes encode varied factors including enzymes for metabolism, cell wall synthesis, transporters, and cell signaling factors. Targeted mutation of the genes validated their roles in GBS resistance to Cu stress. Excepting copA, the genes identified are new to the area of bacterial metal ion intoxication. We conclude that a discrete and limited suite of genes beyond the cop operon in GBS contributes to a repertoire of mechanisms used to survive Cu stress in vitro and achieve cellular homeostasis.

IMPORTANCE Genetic systems for copper (Cu) homeostasis in bacteria, including streptococci, are vital to survive metal ion stress. Genetic systems that underpin survival of GBS during Cu stress, beyond the archetypal cop operon for Cu management, are undefined. We show that Streptococcus resists Cu intoxication by utilizing a discrete and limited suite of genes beyond the cop operon, including several genes that are new to the area of bacterial cell metal ion homeostasis. The Cu resistome of GBS defined here enhances our understanding of metal ion homeostasis in GBS.

INTRODUCTION

In prokaryotic and eukaryotic cells, copper (Cu) is an important cofactor for metalloenzymes (1), but when in excess, Cu can be cytotoxic. In bacteria, Cu intoxication can reflect enzyme inactivation, perturbation of metabolism, and/or redox stress, including a higher potential to generate reactive oxygen species (2). In the context of an infected host, phagocytes such as macrophages and neutrophils can mobilize intracellular pools of Cu to proactively expose internalized bacteria to excess metal to achieve conditions that are antimicrobial (3, 4). Such subcellular areas within infected phagocytes in which concentrated Cu exerts antimicrobial effects have been described for several bacterial pathogens (5, 6). The antimicrobial properties of Cu are thus of interest to the field of infection and immunity since these offer potential avenues for antimicrobial benefit, which might be harnessed to better control bacterial infection (4, 7, 8).

The prototypical system for Cu efflux in bacteria utilizes the cop operon, encompassing copA, which encodes an ATPase efflux pump that extrudes cellular Cu ions, alongside a Cu-specific transcriptional regulator, copY, which represses the operon (9–11). Adaptation to metal excess and limitation in bacteria is nonetheless complex. Several systems additional to the cop operon based on efflux proteins, including P-type ATPases, are also described, and these contribute to bacterial resistance to metal stress for several pathogens, as reviewed elsewhere (5). Streptococcus agalactiae, also known as group B Streptococcus (GBS), is an opportunistic bacterial pathogen of humans and animals for which a discrete genetic system for cellular management of Cu homeostasis based on the cop operon was recently described (12). The GBS cop operon regulates cellular Cu content by responding to excess Cu and derepressing copA via CopY to drive Cu export from the cell (12). A functional system for Cu efflux in GBS was also shown to contribute to virulence of the bacteria during acute infection (12).

Here, we sought to identify genetic systems in addition to the cop operon that aid Cu management in GBS. We used a genome-wide approach based on transposon-directed insertion site sequencing (TraDIS) to probe the GBS genome for regions that support cell survival of Cu stress.

RESULTS

Determination of growth conditions and Cu concentration required for TraDIS.

To probe the entire GBS genome for regions that support the survival of this organism during Cu stress, we first evaluated the conditions for in vitro exposure of GBS to Cu stress, which would be suitable for a subsequent forward genetic screen. To do this, we tested a Cu concentration of 1.5 mM in Todd-Hewitt broth (THB) medium for inhibition of GBS growth because this was sufficient to inhibit a GBS mutant deficient in copA (encoding a Cu efflux P-type ATPase) in a prior study (12). Growth assays verified that 1.5 mM Cu in THB was insufficient to inhibit the growth of wild-type GBS 874391 but sufficient to completely inhibit the growth of a GBS ΔcopA mutant (Fig. 1). The level of 1.5 mM Cu in THB was therefore accepted as suitable to probe for additional genes that contribute to resistance to Cu stress, as this would inhibit growth of mutants sensitive to Cu.

FIG 1.

Growth of WT GBS 874391 and a copA-deficient mutant in Cu stress. The bacteria were grown in THB supplemented with 1.5 mM Cu for 12 h. Points show means for attenuance (D, 600 nm), and bars show standard errors of the means (n = 3).

Identification of genes associated with Cu resistance in GBS 874391.

To facilitate an extensive genome-wide screen of genes required for Cu resistance in GBS 874391, we first generated a library of approximately 480,000 random ISS1 insertional mutants using pGh9-ISS1. Next, we subjected the mutant library to the growth conditions established above to identify genes associated with Cu resistance. In this assay, ∼1.9 × 10⁸ cells (equating to approximately 400 cells per unique mutation) from the library were inoculated in triplicate into 100 mL of either THB supplemented with 1.5 mM Cu (test pool) or THB without Cu supplementation (control pool) and incubated for 12 h at 37°C. These conditions were chosen to permit the growth of mutants unaffected by Cu but inhibit growth of mutants sensitive to Cu (such as for the ΔcopA mutant above). Genomic DNA was extracted from each replicate and sequenced with a multiplex TraDIS approach (Fig. 2A). The control pool yielded a total of 5,163,397 ISS1-specific reads that mapped to the 874391 genome. Further analysis of the control data revealed 618,263 unique insertion sites (approximately one insertion site every 4 bp) distributed across the entire chromosome (see Fig. S1 in the supplemental material), highlighting the high degree of saturation and coverage of our library.

FIG 2.

Defining the Cu resistome of GBS using TraDIS. (A) Experimental design to identify genes associated with Cu stress. A supersaturated GBS ISS1 library is inoculated into THB (Ctrl) or THB plus 1.5 mM Cu (+Cu) and grown for 12 h to stationary phase. Bacterial genomic DNA is then extracted and subjected to sequencing and TraDIS analysis. (B) TraDIS analysis of the GBS Cu resistome identified 5 genes that were significantly overrepresented (blue) and 8 genes that were significantly underrepresented (red), using highly stringent cutoffs (2 ≤ log₂FC ≤ −2; FDR < 0.001 and P value < 0.05). A further 28 and 15 genes were significantly under- or overrepresented between 2- and 4-fold (log₂FC ± 1 to 2), respectively. Horizontal dashed lines highlight FC cutoffs of 2 ≤ log₂FC ≤ −2, and solid lines indicate cutoffs of 1 ≤ log₂FC ≤ −1.

As mutants with insertions in genes required for Cu resistance would be lost and underrepresented, we screened for a loss of insertions in the test pool compared to the control pool. Using stringent selection criteria of a log₂ fold change (log₂FC) in read counts of ≤−2, false-discovery rate (FDR) of <0.001, and P value of <0.05, we identified a hit plot of genes that contributed to GBS growth in Cu stress (Fig. 2B). Here, we identified eight genes as highly significantly underrepresented in the data set (Table 1). Consistent with previous reports of a requirement for copA in resisting Cu stress, copA was significantly underrepresented (∼16-fold down) during Cu stress, representing validation for the TraDIS approach. Interestingly, we also identified five genes that possessed an enrichment of read counts (log₂FC of ≥2) in the test pool compared to the control pool, suggesting that insertions in these genes were beneficial for growth under Cu stress (Table 1). Representative insertion site mapping is shown for a selection of loci (Fig. 3A to F). We also noted a further 28 and 15 genes that were underrepresented and overrepresented in the data set (log₂FC between −1 and −2 or between 1 and 2 [Table S1]), respectively. Interestingly, this list included two genes (rfaB [log₂FC = −1.24] and plyB [log₂FC = −1.63]) which we have found to contribute to zinc resistance (M Sullivan, K Goh, and G Ulett, unpublished data). Hence, we chose to include these two genes in subsequent experiments as representative members of the group of 28 genes significantly underrepresented in the Cu stress pool between 2- and 4-fold.

TABLE 1.

Genes identified in TraDIS screen as significantly underrepresented and overrepresented

Locus taga	Gene	Annotation	Log2FC	Log2cpm
01047	hisM b	Amino acid ABC transporter permease	−6.41	7.63
01048	hisJ b	Amino acid ABC transporter ATP-binding protein	−6.37	7.37
01049	hisP b	Amino acid ABC transporter substrate-binding protein	−4.94	7.98
00507	copA	Cu-translocating P-type ATPase	−3.98	9.27
00084	oafA b	Acyltransferase	−3.80	11.04
00083		Membrane protein	−3.78	9.02
01646	yceG b	MltG-like endolytic transglycosylase	−3.64	5.80
00435	stp1 b	Stp1/IreP family PP2C-type Ser/Thr phosphatase	−2.10	5.96
00288	ackA	Acetate kinase	2.04	7.22
00879	ribH	6- and 7-dimethyl-8-ribityllumazine synthase	2.40	7.98
00877	ribE	Riboflavin synthase	2.46	8.12
00876	ribD b	Bifunctional diamino-hydroxyphospho-ribosyl-amino-pyrimidine deaminase/5-amino-6-(5-phosphoribosylamino) uracil reductase RibD	2.67	9.19
00878	ribA	Bifunctional 3- and 4-dihydroxy-2-butanone-4-phosphate synthase/GTP cyclohydrolase II	2.74	9.00

^aDenotes GBS strain 874391 locus tag, preceded by CHF17_.

^bGenes that were mutated for this study.

FIG 3.

Insertion plots of genes associated with Cu resistance as identified by TraDIS. Individual insertions mapped to the copYAZ (A), hisMJP (B), oafA (C), stp1 (D), yceG (E), and ribDEAH (F) loci are shown, with vertical dotted lines denoting the boundaries of each genetic element. The number of reads mapped per base pair is shown in the nonexposed control in gray and in the Cu stress condition in blue. Genes without annotation are identified by the GBS strain 874391 locus tag numbers (i.e., CHF17_00082, CHF17_00083, CHF17_01645).

Characterization and validation of Cu-sensitive mutants.

To validate hits from the TraDIS screen, we generated targeted isogenic mutants of several candidate genes and phenotypically analyzed these mutants for survival and growth in Cu stress. The genes included hisMJP (CHF17_01047, 01048, and 01049), oafA (CHF17_00084), yceG (CHF17_01646), stp1 (CHF17_00435), ribD (CHF17_00876), rfaB (CHF17_00838), and plyB (CHF17_00885). First, CFU assays based on the conditions used for the TraDIS screen were performed to test survival of the mutants in 1.5 mM Cu after a 12 h incubation period. In this assay, besides wild type (WT) and the ΔhisMJP mutant, all other isogenic mutants exhibited a significant decrease (∼30% to 72%) in CFU counts when grown in the presence of Cu, indicating that these mutants were sensitive to Cu (Fig. 4). Notably, we also observed significantly lower overall bacterial counts of the ΔplyB and Δstp1 mutants compared to WT when grown in THB, indicating that these genes may contribute to the growth of GBS in rich media.

FIG 4.

Viability analysis of WT GBS and isogenic mutants targeted for genes that contribute to resistance to Cu stress in THB media. CFU assays of WT GBS and isogenic mutants grown in THB or THB plus 1.5 mM Cu for 12 h. P values calculated with independent t tests comparing THB and THB plus 1.5 mM Cu (***, P < 0.001; **, P < 0.01; *, P < 0.05; ns, not significant). Data are means from 3 independent repeats with error bars indicating standard errors of the means.

We further explored the Cu sensitivity of the mutants by measuring growth kinetics over 12 h in THB medium with and without supplemental 1.5 mM Cu. First, there was no significant difference in the growth kinetics of the mutant strains compared to WT in the control condition, THB (Fig. 5A), excepting the ΔrfaB and ΔribD mutants, which were significantly attenuated or enhanced, respectively (Fig. 5B). In these comparisons, the attenuated growth kinetics of the Δstp1 mutant approached statistical significance (P = 0.054). Next, the ΔribD mutant grew to higher culture densities than WT during stationary-phase Cu stress conditions, with final attenuance (D; 600 nm) values (at 12 h) being significantly higher (Fig. S2). The ΔhisMJP strain also exhibited significantly higher final D 600 nm values (at 12 h) compared to WT (Fig. S2). In THB with Cu, the ΔoafA, ΔhisMJP, ΔplyB, ΔrfaB, and Δstp1 mutants exhibited attenuated growth compared to WT (Fig. 5C). Finally, the ΔhisMJP, ΔoafA, ΔyceG, and Δstp1 mutants were significantly attenuated for growth during Cu stress, with lower overall absorbance, or an extended lag phase, compared to control conditions (of the same strain in THB without Cu stress). Complementation of the ΔhisMJP, ΔyceG, and Δstp1 mutants in trans and subsequent growth assays showed nearly complete restoration of growth in Cu stress to non-Cu stress conditions (Fig. S3).

FIG 5.

Growth kinetics of GBS and isogenic mutants in THB medium with and without Cu stress. (A) Growth curves of GBS and derivative mutants in THB plus 1.5 mM Cu (Cu stress; blue lines) compared to THB alone (control; black lines). Data are compiled from measurements of attenuance (D, 600 nm) every 30 min with solid lines as means and shaded areas indicating standard errors of the means from ≥3 independent experiments. Cu stress data for each strain were compared to control data using area under the curve (AUC) analysis followed by independent t tests with significance indicated at the top right of each panel. (B and C) The growth kinetics of the WT strain were compared to each of the isogenic mutant strains using AUC and independent t tests in THB (B) (control, black) and in THB plus 1.5 mM Cu (C) (Cu stress, blue) (*, P < 0.05; **, P < 0.01; ***, P < 0.005).

We and others have previously reported that culture media can affect sensitivity of streptococci to Cu (11, 12). Consequently, we measured the growth of WT GBS and each isogenic mutant in nutrient limited conditions using a minimal chemically defined medium (CDM) with and without supplemental Cu (Fig. 6A). In these assays, growth of the WT strain was unaffected by the presence of 0.5 mM Cu in CDM (Fig. 6A; additional Cu concentrations of 0.2 mM and 1.0 mM shown in Fig. S4). Several mutants (ΔhisMJP, ΔplyB, ΔrfaB, and Δstp1) exhibited significant growth defects in CDM in the absence of Cu compared to WT (Fig. 6B). In CDM with Cu, all mutants except the ΔribD strain exhibited significantly attenuated growth compared to WT (Fig. 6C). Additionally, apart from the ΔribD strain, growth of all other mutants (ΔhisMJP, ΔoafA, ΔyceG, ΔplyB, ΔrfaB, and Δstp1) was significantly attenuated compared to control conditions of the same strain in CDM without Cu stress (Fig. 6A). Notably, the attenuated growth phenotypes of each of the mutants (excepting the ΔribD strain) due to Cu stress were more severe in CDM than in THB. Complementation of the ΔhisMJP, ΔyceG, ΔrfaB, and Δstp1 mutants in trans showed restoration of growth in Cu stress (Fig. S5). Interestingly, complementation of the ΔplyB mutant showed further attenuation of growth when under Cu stress.

FIG 6.

Growth kinetics of GBS and isogenic mutants in CDM with and without Cu stress. (A) Growth curves of GBS and derivative mutants in CDM plus 0.5 mM Cu (Cu stress; blue lines) compared to CDM alone (control; black lines). Data are compiled from measurements of attenuance (D, 600 nm) every 30 min with solid lines as means and shaded areas indicating standard errors of the means from ≥3 independent experiments. Cu stress data for each strain were compared to control data using area under the curve (AUC) analysis followed by independent t tests with significance indicated at the top right of each panel. (B and C) The growth kinetics of the WT strain were compared to each of the isogenic mutant strains using AUC and independent t tests in CDM (B) (control, black) and in CDM plus 0.5 mM Cu (C) (Cu stress, blue) (*, P < 0.05; **, P < 0.01; ***, P < 0.005).

Despite numerous attempts, we were unable to generate an oafA plasmid construct for complementation studies. Hence, we used a chelator to further probe the role of oafA in Cu tolerance. To this end, we performed growth assays in CDM (with or without Cu) with various amounts of TPEN [N,N,N′,N′-tetrakis(2-pyridylmethyl)ethylenediamine]. Here, we found that growth of the ΔoafA mutant was partially restored upon addition of TPEN (Fig. S6). Taken together, these data support the observations made using our TraDIS analyses to confirm major contributions of several novel genes to tolerance of Cu stress in streptococci.

Accumulation of intracellular Cu during Cu stress.

Inductively coupled plasma optical emission spectroscopy (ICP-OES) was used to investigate if cellular Cu content is affected in each respective isogenic mutant. Standard THB medium contains 0.2 ± 0.08 μM Cu, reflecting trace amounts in the medium (12). Our approach to quantify intracellular Cu at mid-exponential growth phase under conditions of Cu stress that are subinhibitory for WT and mutants was consistent with our previous study. To this end, cultures of WT and the respective mutants were grown for 2.5 h in THB or in THB supplemented with 0.5 mM Cu. In the absence of supplemental Cu, WT GBS limited intracellular Cu content such that only 0.53 ± 0.04 μg Cu g dry weight⁻¹ were detected in cultures grown in THB, consistent with prior findings (12). Growth of WT in the presence of 0.5 mM Cu resulted in a significant increase in intracellular Cu, to 11.69 ± 3.52 μg per g dry weight (Fig. 7A). A similar pattern was observed in the different mutants, where exposure to Cu also resulted in a significant increase in intracellular Cu (Fig. 7A). Strikingly, the Δstp1 mutant exhibited almost twice as much intracellular Cu as did WT (20.89 ± 5.85 μg Cu g dry weight⁻¹), whereas the ΔhisMJP, ΔribD, and ΔrfaB mutants contained approximately half the intracellular Cu of WT (4.34 ± 1.57, 5.89 ± 1.68, and 6.61 ± 0.77 μg Cu g dry weight^−1, respectively) (Fig. 7B). There was no significant alteration in the intracellular Cu content for the ΔyceG, ΔplyB, and ΔoafA mutants compared to WT. A summary of the results from this study is presented in Table S2.

FIG 7.

Intracellular Cu content in WT GBS 874391 and isogenic mutants in Cu stress. (A) Total intracellular Cu contents were compared in WT and isogenic mutants grown in THB with and without supplemental Cu (0.5 mM) and normalized using dry weight biomass (μg Cu per mg). (B) Ratio of intracellular Cu content in isogenic mutants compared to WT in Cu stress. Data presented are means from 3 independent repeats with error bars indicating standard errors of the means and compared by independent t tests (ns, not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.005).

DISCUSSION

GBS is an opportunistic pathogen that causes a diverse range of disease etiologies in infants and adults, including skin and soft tissue infections, arthritis, pneumonia, meningitis, urinary tract infection, and endocarditis (13). GBS expresses several virulence factors that enable the bacteria to survive under harsh conditions, such as acid stress and oxidative stress and during infection of a host, as reviewed elsewhere (14). Metal ion stress due to excess Cu was recently demonstrated to be antimicrobial toward GBS (12). Cu is an essential micronutrient for bacteria (15), but as excess Cu can be toxic to cells, bacteria need to regulate the amount of intracellular Cu during Cu stress. This can be achieved using three mechanisms—(i) expulsion of intracellular Cu into the extracellular milieu, (ii) sequestration of Cu by Cu binding proteins, and (iii) oxidation of Cu(I) to the less toxic form of Cu(II) (16). In this study, using a forward genetic screen based on TraDIS, we identify new GBS factors that contribute significantly to the survival and growth of this pathogen under Cu stress conditions. The key findings are that (i) GBS utilizes several genes in addition to the cop operon to manage Cu homeostasis during Cu stress and (ii) the GBS Cu stress resistome comprises principally eight genes that are required for GBS to resist Cu stress, including hisMJP, oafA, yceG, plyB, rfaB, and stp1. These genes have not previously been linked to mechanisms of bacterial resistance to Cu stress.

As a screening approach to identify novel functions of bacterial genes, TraDIS has been used to explore GBS survival in blood, which revealed protective effects of calprotectin (17–19). TraDIS analysis in the current study identified novel functions of several genes in GBS that play a role in Cu resistance. Our approach was validated through the identification of copA in our TraDIS screen, which encodes an exporter known to be essential for GBS Cu resistance (12). We generated defined mutants for eight other genes (with ΔhisMJP generated as a single mutant). There was a broad range of putative functions associated with these genes, including cell wall biogenesis (oafA, plyB, yceG, and rfaB), metabolism (hisMJP and ribD), and signal transduction (stp1). It is perhaps unsurprising that we saw a diverse range of phenotypes among the isogenic deletion mutants, depending on the phenotypic assays used. Our quantitation of viable bacteria at 12 h following exposure to 1.5 mM Cu showed lower recovery of the ΔyceG, ΔplyB, ΔrfaB, and Δstp1 mutants, which matches the underrepresentation of insertional mutations in these genes in our TraDIS screen under this condition at this time point. We also noted a reduction in CFU counts in the ΔribD strain under these conditions, in contrast to the significant overrepresentation of insert counts in this locus in the TraDIS screen. Similarly, we observed no difference in CFU values of the ΔhisMJP strain in comparing Cu stress to the control (no Cu stress); noting this was the most significantly underrepresented gene cluster in our TraDIS data set. We suggest that these differences may result from differences in assay design, readout, and interpretation, rather than reflecting confliction of biological responses of the bacteria. For example, attenuance readings may not correlate with CFU estimates due to the presence of live and dead bacteria in different growth phases or the insertional frequency observed in TraDIS due to fundamental differences in assay design.

Measurements of the growth kinetics of each isogenic mutant in THB or CDM showed marked attenuation compared to WT, excepting the ribD strain, based on cumulative area under the curve (AUC) analysis of attenuance values over the 12 h period. These findings also show enhanced sensitivity of the mutants to Cu in a medium-dependent manner, suggesting that nutrient availability can affect Cu sensitivity in an indirect manner and that this requires further study. The exact mechanisms by which these genes facilitate resistance to Cu toxicity are yet to be elucidated.

Stp1 is a serine/threonine phosphatase and is important for regulation of its cognate kinase partner Stk1 and GBS virulence, serving as a master controller of numerous cellular processes including nucleotide metabolism, cell segregation, and virulence (20, 21). The Stp1/Stk1 axis feeds into virulence regulation through direct phosphorylation and inactivation of CovR (22). We found that not only is the stp1 mutant more sensitive to Cu stress but it also accumulates twice as much Cu as does WT in Cu stress. In GBS, mutation of stp1 leads to alterations in phosphorylation of a number of proteins, which in turn affect gene expression (20, 23). Genes differentially expressed as a result of stp1 mutation include several ABC transporters implicated in the uptake of amino acids and metal transport (20), including upregulation of hisP (identified in this study) and downregulation of mtsABC encoding a putative Mn transport system that is modulated by Cu or Zn stress in GBS (12, 24). Indeed, Stp1 is a Mn-dependent phosphatase; free Cu may displace Mn from the protein and lead to lower/abolished activity, providing circumstantial clues to explain the Cu sensitivity phenotype we observed in the stp1 mutant. For example, the enhanced sensitivity of the Stp1 mutant to Cu stress may be due to abrogation of Mn homeostasis and disruption of nucleotide metabolism (25, 26). However, the propensity for Cu to displace Mn in free proteins, although discussed elsewhere (11, 27), is not well defined. The pleiotropic nature of Stp1-mediated processes means that the exact mechanism underpinning the contribution of Stp1 to Cu resistance in GBS remains to be determined.

HisMJP encodes a putative amino acid ABC transport system in GBS. Structural modeling with Phyre2 (28) revealed that HisP shares high predicted structural similarity with a ratified ABC transporter substrate binding protein of Streptococcus pneumoniae bound to histidine (Protein Data Bank https://www.rcsb.org/ entry 4OHN). Cu sequestration by Cu-binding proteins is a mechanism bacteria employ to subvert Cu toxicity, and Cu-binding sites in proteins are dominated by histidine, cysteine, and methionine residues, with Cu(II) having affinity for histidine (29). GBS is a histidine auxotroph and overcomes this by using two different mechanisms: by importing histidine from the environment (potentially via HisMJP) or by importing peptides via permeases, which are then subsequently cleaved by peptidases into single amino acids (30, 31). It may be that GBS deficient in hisMJP lacks the ability to import histidine and that this causes a metabolic shift that requires the bacteria to obtain this essential amino acid from alternative sources, such as from peptides present in THB. Our data support this hypothesis; the ΔhisMJP mutant reaches a similar CFU and absorbance as those of the WT after 12 h of growth in THB plus 1.5 mM Cu; however, there is a significant lag phase, during which cells may undergo a metabolic switch. However, when the ΔhisMJP mutant is incubated in minimal CDM plus 0.5 mM Cu, which lacks peptide supplements, growth is abrogated. Interestingly, the ΔhisMJP mutant possessed the least amount of total intracellular Cu when subjected to Cu stress in THB, which hints at a potential Cu-import role for this putative histidine transport system, perhaps via import of Cu-histidine complexes (32) in the extracellular milieu.

We identified several genes, including ribD, ribE, ribA, and ribH, which were significantly overrepresented in the TraDIS data set, suggesting their mutation may be of benefit to Cu tolerance. In GBS, ribDEAH encode a synthesis pathway for riboflavin which is required for flavin adenine dinucleotide (FAD) and flavin mononucleotide (FMN) cofactor production. Generation and analysis of an isogenic mutant in the promoter-proximal gene of the putative ribDEAH operon, ribD, showed enhanced growth of the mutant in THB compared to WT (in the absence of Cu) but no difference from WT in THB plus 1.5 mM Cu or under either condition in CDM. In our present study, we could not prescribe a role for ribD relating to Cu stress, but we do not believe our TraDIS identification of rib genes serves as a false-positive result. For example, insertion of the ∼4.6-kb pGh9:ISS1 element (33) in the assay would cause polar effects on the entire rib operon. In our ΔribD mutant, we targeted 1,038 bp for removal, representing an in-frame, markerless, nonpolar deletion (of ∼94% of ribD). Thus, the type of mutation we made in ribD in this instance is not identical to the type of mutation generated by ISS1 insertion and TraDIS analysis. Moreover, in a prior study of Staphylococcus aureus (34), ribD was found to be downregulated in response to Cu stress, supporting our belief that ribD is not a false positive from our genetic screen. Nevertheless, future work to dissect the contribution of the rib locus to Cu stress resistance is now warranted.

Establishing a new collection of genes that confer GBS resistance to Cu stress expands our understanding of metal management in this organism and offers new insight into the genetic diversity mediating resistance to Cu intoxication in bacteria. For example, genes encoding enzymes for metabolism and cell wall synthesis, regulators, and transporters are critical for GBS to resist Cu stress. Four genes identified in the current study (oafA, rfaB, plyB, and yceG) possess domains that are commonly found in proteins involved in cell wall biogenesis. Only mutation in rfaB (encoding a putative glycosyltransferase that may transfer sugar moieties to lipid, protein, or carbohydrate residues) resulted in a reduction in cellular Cu content compared to WT during Cu stress. This finding leads us to present a model in which rfaB supports the central role of copA (12) in cellular Cu management in GBS. Based on Cu content data, the products of plyB, oafA, and yceG do not contribute to cellular Cu status. As such, their exact contributions to resisting Cu stress remain complex and require further characterization. It is notable that in complementing our isogenic mutations, we could not successfully obtain a clone of oafA using Escherichia coli as a cloning host. Instead, we used chelation as an approach to restore growth of our oafA-deficient strain during Cu stress. Interestingly, we also note that complementation in trans with plyB further abrogated growth in Cu stress, suggesting that multiple copies of plasmid-borne plyB may have a detrimental effect on GBS growth. Future studies characterizing the exact functions of the rfaB, plyB, yceG, and oafA genes will help to elucidate mechanistic roles such as in restricting Cu import or compensating for pathways that are susceptible to Cu poisoning. Such work will yield new understanding of the cellular processes that underpin bacterial resistance to Cu intoxication.

Bacterial resistance to metal stress is a fitness trait of some pathogens that is used to evade host defense responses (35, 36), and several studies have shown that Cu management contributes to bacterial pathogenicity. For example, S. pneumoniae regulates central metabolism in response to metal stress to support its survival (17) and uses CopA for virulence during infection (10). In E. coli, Cu-transporting ATPases, including CopA, are required for survival in macrophages (37). We recently demonstrated that copA contributes to the ability for GBS to colonize and survive in the mammalian host during acute infection (12). Together, these studies and the results of the current work show that Cu management is an important facet in various bacterial pathogens, including GBS, in their ability to infect a host. Other observations of bacterial pathogens support a role for Cu management in bacterial virulence in host niches. For example, increased expression of copY in S. pneumoniae in the lungs of mice was reported (10), and higher Cu levels along with coincidental upregulation of copYAZ in the blood of mice infected with Streptococcus pyogenes was reported (11). Characterization of the contributions of the genes of the Cu resistome identified in this current study to GBS virulence will be important to explore potential roles in pathogenesis.

Overall, our application of a highly saturated mutant library combined with deep sequencing provides valuable insight into the Cu stress resistome of GBS. Our study identifies a unique collection of genetic targets (including hisMJP, oafA, yceG, plyB, ribD, rfaB, and stp1) that are new to the field of metal detoxification in bacteria, and it will be of interest to study their effects toward resistance to metal stress in other pathogens. Together, these findings provide new insight into the repertoire of mechanisms used by GBS to survive Cu stress, which may be relevant to other bacteria.

MATERIALS AND METHODS

Bacterial strains, plasmids, and growth conditions.

GBS and E. coli strains and plasmids used are listed in Table S3 in the supplemental material. GBS was routinely grown in Todd-Hewitt broth (THB) or on TH agar (1.5% [wt/vol]). E. coli was grown in lysogeny broth (LB) or on LB agar. Routine retrospective colony counts were performed by plating dilutions of bacteria on tryptone soya agar containing 5% defibrinated horse blood (Thermo Fisher Scientific). Media were supplemented with antibiotics (spectinomycin [Sp], 100 μg/mL), as indicated. Growth assays used 200-μL culture volumes in 96-well plates (Greiner) sealed using Breathe-Easy membranes (Sigma-Aldrich) and measured attenuance (D, at 600 nm) using a ClarioSTAR multimode plate reader (BMG Labtech) in Well Scan mode using a 3-mm 5 × 5 scan matrix with 5 flashes per scan point and path length correction of 5.88 mm, with agitation at 300 rpm and recordings taken every 30 min. Media for growth assays were THB, a modified chemically defined medium (CDM) (24) (with 1 g/L glucose, 0.11 g/L pyruvate, and 50 mg/L l-cysteine), supplemented with Cu (supplied as CuSO₄) and/or TPEN [N,N,N′,N′-tetrakis(2-pyridylmethyl)ethylenediamine; Sigma-Aldrich] as indicated. For attenuance baseline correction, control wells without bacteria were included for Cu in medium alone.

DNA extraction and genetic modification of GBS.

Plasmid DNA was isolated using miniprep kits (Qiagen), with modifications for GBS as described elsewhere (38). All strains and primers used are listed in Tables S3 and S4, respectively. Mutant strains were constructed via markerless allelic exchange using sequences (Table S5) first synthesized in pUC57 (GenScript, USA) and subcloned into pHY304aad9 as previously described (24). Complement constructs were made by cloning the respective genes into shuttle vector pDL278. Mutants and complement constructs were validated by PCR using primers external to the mutation/cloning site and DNA sequencing.

Whole-bacterial-cell metal content determination.

Metal content in cells was determined as described previously (39). Cultures were prepared essentially as described previously (12); THB medium was supplemented with 0.5 mM Cu or not supplemented (Ctrl), and following exposure for 2.5 h, bacteria were harvested by centrifugation at 4,122 × g at 4°C. Cell pellets were washed 3 times in phosphate-buffered saline (PBS) plus 5 mM EDTA to remove extracellular metals, followed by 3 washes in PBS. Pelleted cells were dried overnight at 80°C, resuspended in 1 mL of 32.5% nitric acid, and incubated at 95°C for 1 h. The metal ion-containing supernatant was collected by centrifugation (14,000 × g, 30 min) and diluted to a final concentration of 3.25% nitric acid for metal content determination using inductively coupled plasma optical emission spectroscopy (ICP-OES). ICP-OES was carried out on an Agilent 720 ICP-OES with axial torch, OneNeb concentric nebulizer, and Agilent single-pass glass cyclone spray chamber. The power was 1.4 kW with 0.75 L/min nebulizer gas, 15 L/min plasma gas, and 1.5 L/min auxiliary gas flow. Cu was analyzed at 324.75 nm, Zn at 213.85 nm, Fe at 259.94 nm, and Mn at 257.61 nm with detection limits at <1.1 ppm. The final quantity of each metal was normalized using dry weight biomass of the cell pellet prior to nitric acid digestion, expressed as μg · g⁻¹ dry weight. Scandium was used as an internal standard for quality control in recovery in the ICP-OES analyses; recovery was >97% for all samples.

Transposon-directed insertion site sequencing (TraDIS).

Generation and screening of the 874391:ISS1 library was performed essentially as previously described (40), with some modifications. Briefly, the pGh9:ISS1 plasmid (33) (provided by A. Charbonneau et al.) was transformed into WT GBS, and successful transformants were selected by growth on THB agar supplemented with 0.5 μg/mL erythromycin (Em). A single colony was picked and grown in 10 mL of THB with 0.5 μg/mL Em at 28°C overnight. The overnight cultures were incubated at 40°C for 3 h to facilitate random transposition of ISS1 into the bacterial chromosome. Transposon mutants were selected by plating cultures onto THB agar supplemented with Em and growing them overnight at 37°C. Pools of the transposon mutants were harvested with a sterile spreader and stored in THB supplemented with 25% glycerol at −80°C. The final library of approximately 480,000 mutants was generated by pooling two independent batches of mutants.

Exposure of the library used approximately 1.9 × 10⁸ bacteria inoculated into 100 mL of THB (nonexposed control) or THB supplemented with 1.5 mM Cu in THB. The cultures were grown for 12 h at 37°C (shaking), and subsequently, 10 mL of culture was removed and washed once with PBS. Genomic DNA was extracted from three cell pellets per condition (prepared as independent biological samples) using the DNeasy UltraClean microbial kit (Qiagen) according to the manufacturer’s instructions, except that the cell pellets were incubated with 100 units of mutanolysin and 40 mg of RNase A at 37°C for 90 min.

Genomic DNA was subjected to library preparation as previously described (29), with slight modifications. Briefly, the NEBNext double-stranded DNA (dsDNA) Fragmentase (New England BioLabs) was used to generate DNA fragments in the range of 200 to 800 bp. An in-house Y-adaptor was generated by mixing and incubating adaptor primers 1 and 2 for 2 min at 95°C and chilling the reaction mixture to 20°C by incremental decreases in temperature by 0.1°C. The reaction mixture was placed on ice for 5 min, and ice-cold ultrapure water was added to dilute the reaction mixture to 15 μM. The Y-adaptor was ligated to the ends of the fragments using the NEBNext Ultra II DNA library prep kit for Illumina (New England BioLabs) according to the manufacturer’s instructions. All adaptor-ligated fragments were incubated with NotI.HF (New England BioLabs) for 2 h at 37°C to deplete plasmid fragments. The digested fragments were PCR amplified per the protocol outlined in the NEBNext Ultra II DNA library prep kit using a specific ISS1 primer and reverse indexing primer. DNA quantification was undertaken using a Qubit dsDNA HS assay kit (Invitrogen) and purified using AMPure XP magnetic beads (Beckman Coulter). All libraries were pooled and submitted for sequencing on the MiSeq platform at the Australian Centre for Ecogenomics (University of Queensland, Australia).

The sequencing data generated from TraDIS libraries were analyzed using the Bio-TraDIS scripts (41) on raw demultiplexed sequencing reads. Reads containing the transposon tag (CAGAAAACTTTGCAACAGAACC) were filtered and mapped to the genome of WT GBS 874391 using the bacteria_tradis script with the “--smalt_y 1” and “--smalt_r 0” parameters to ensure accuracy of insertion mapping. Subsequent analysis steps to determine log₂ fold change (log₂FC), false-discovery rate (FDR), and P value were carried out with the AlbaTraDIS script (42). To identify genes in 874391 required for resistance to the Cu intoxication condition used, we used stringent criteria of log₂FC of ≤−2 or ≥2, FDR of <0.001, and P value of <0.05.

Statistical methods.

All statistical analyses used GraphPad Prism V8 and are defined in the respective figure legends. Statistical significance was accepted at P values of ≤0.05.

Data availability.

The TraDIS reads are deposited in the Sequence Read Archive (SRA) under BioProject ID PRJNA674399.