Proteomic Evidence for Biofilm‐Mediated Copper Stress Adaptation in Oleidesulfovibrio alaskensis G20

ABSTRACT

Copper (Cu) is an essential cofactor for enzymes regulating key metabolic processes; however, excess Cu can inhibit bacterial growth. The ability of Oleidesulfovibrio alaskensis G20 (OA G20) to survive under heavy metal stress is compelling. Our previous study on OA G20 exposed to Cu suggests that bacteria might use biofilm formation to adapt to high levels of toxic metal ions. To elucidate the molecular mechanisms underlying this adaptation, we performed a comparative proteomic analysis of OA G20 stress‐induced biofilms (30 μM Cu) versus control (no Cu) and their respective extracellular fractions. Proteomic analysis revealed that among the differentially regulated intracellular proteins identified in this study, 47.93% were upregulated and 52.07% were downregulated in OA G20 biofilms exposed to 30 μM Cu compared to control. Similarly, 41.05% of extracellular proteins were upregulated and 58.95% were downregulated. The significantly modulated proteins (log2FC > 1) were involved in heavy‐metal ion transportation, cell division, chemotaxis, cell motility and cell morphology. Our results also identified 133 hypothetical proteins under copper stress, several of which were related to prokaryotic membrane lipoprotein, cell and flagellar motility, and Type VI secretion system, offering new avenues for future research in bioremediation and biofilm mitigation strategies in industrial settings.

OA G20 differentially regulates protein expression involved in key metabolic pathways, including two‐component systems, ABC‐transporters, chemotaxis, quorum sensing and flagellar assembly to overcome copper stress.

1. Introduction

Oleidesulfovibrio alaskensis G20 (OA G20), a biofilm‐forming anaerobic sulphate‐reducing bacterium (SRB), is well known to play a key role in the biogeochemical cycling of carbon and sulphur (Price et al. 2014). SRB have garnered significant attention in industrial settings due to their dual role, contributing to biotechnological applications while also causing infrastructure deterioration (Novair et al. 2024). Desulfovibrio species pose significant challenges as they are key players in causing the souring of petroleum and metal corrosion, also known as microbial‐induced corrosion (MIC) or biocorrosion (Hamilton 2003). However, they are also a potential candidate for bioremediation of metal‐contaminated sites (Keller et al. 2014), due to their ability to reduce heavy metals and radionuclides, including uranium and chromium (Lovley et al. 1991; Sani et al. 2004), and precipitate metal, such as Cu (Hu et al. 2016; Li et al. 2018) and cadmium (Liao et al. 2024), to insoluble metal sulphides.

Cu in trace amounts supports the activity of electron transport and redox reactions (Itoh 2024). Although an essential micronutrient, heavy metal ions are toxic to bacteria at elevated concentrations. The toxic nature of Cu can be attributed to its ability to damage cellular macromolecules by the generation of reactive oxygen species (ROS), the mismetallation of iron and manganese‐containing proteins, and the ability to render an enzyme inactive by replacing metal cofactors from their active sites (Gautam et al. 2023; Husain and Mahmood 2019; Rademacher and Masepohl 2012).

SRB employs a plethora of heavy metal resistance mechanisms, including biofilm formation, metal efflux, hydrogen sulphide production, enzyme detoxification and metal sequestration (Raya et al. 2022; Argüello et al. 2013; Bachenheimer and Bennett 1961; Li, You, et al. 2022; Solioz and Solioz 2018; Solioz 2018). Of specific interest is the ability of OA G20 to form biofilms: surface‐attached cells embedded within a self‐produced matrix. Biofilm formation provides bacteria with a protective environment, allowing the bacteria to survive under metal or antibiotic stress, rapid changes in nutrients, pH, temperature and osmolarity (Clark et al. 2012). In addition, biofilm formation in bacteria involves altered gene expression compared to its planktonic counterparts, suggesting it is a highly intricate and regulated process (Qi et al. 2016). SRB biofilms have previously been investigated in the context of heavy metal ion treatment (Jin et al. 2007; White and Gadd 1998, 2000; Thakur et al. 2024; Fang et al. 2002). For instance, when exposed to heavy metal ions like Cu and cadmium, SRB showed an increase in biofilm and extracellular polymeric substance (EPS) biosynthesis, suggesting they play a significant role in bacterial protection under metal ion stress (White and Gadd 1998, 2000). The protective role of biofilms can be attributed to their ability to capture metal ions through EPS (Li, Deng, et al. 2022). Various studies on SRB biofilms indicate that EPS mainly consists of proteins, with minimum levels of exopolysaccharide (Thakur et al. 2024; Clark et al. 2007), compared to other bacterial species where the biofilm matrix is predominantly made of carbohydrates and/or nucleic acids (Wang et al. 2021; Friedman and Kolter 2004; Wickramasinghe et al. 2020). Bacteria, when exposed to unfavourable conditions, can alter their EPS composition to adapt to stressful environments (Lian et al. 2022; Wang et al. 2023).

The effect of Cu ions on the planktonic growth of OA G20 and its biofilm formation has been previously explored by our group (Thakur et al. 2024; Tripathi et al. 2022). For example, Tripathi et al. (Tripathi et al. 2022) reported modulation of several metabolic pathways like energy conservation, disruption in metal‐homeostasis of other heavy metals, and regulation of transporter complexes when planktonic OA G20 were subjected to Cu stress. Furthermore, the effect of Cu on OA G20 was further studied by Thakur et al. (Thakur et al. 2024) where the influence of high Cu levels was tested on the OA G20 biofilm formation. Albeit these studies provide insights into planktonic cell response and the physiological effect of Cu on biofilm growth, little is known about the molecular responses triggered by OA G20 to overcome Cu stress.

To understand the molecular mechanisms of OA G20 survival under toxic Cu concentrations of 30 μM and the development of biofilms under these conditions, we conducted proteomic analysis of intracellular and extracellular protein fractions from OA G20 biofilms. We employed bioinformatics tools like KEGG and UniProtKB to conduct pathway enrichment and network analyses of our proteomics data. Our findings indicated that OA G20 intracellular and extracellular protein fractions showed altered protein abundances involved in stress response, efflux and transporter proteins, lipopolysaccharide and lipid transport, flagellum and motility, and proteins involved in chemotaxis. These pathway analyses allowed us to identify key metabolic pathways that are regulated in response to Cu stress in both intracellular and extracellular fractions. Proteomic analysis of OA G20 under Cu stress may help develop strategies to either mitigate MIC or enhance their bioremediation potential.

2. Methodology

2.1. Bacterial Growth and Culture Maintenance

The OA G20 strain was a generous gift from Dr. Judy Wall, Department of Biochemistry, University of Missouri, and has been maintained in the laboratory of Dr. Rajesh K. Sani at South Dakota Mines. OA G20 was grown in a lactate‐C medium (Tripathi et al. 2022). Lactate‐C medium consists of 20.57 mM sodium lactate, 31.68 mM Na₂SO₄, 0.54 mM CaCl₂, 1.02 mM Na₃C₆H₅O₇.2H₂O, 18.70 mM NH₄Cl, 16.62 mM MgSO₄, 3.67 mM KH₂PO₄, 0.57 mM C₆H₈O₆, 0.88 mM C₂H₃NaO₂S, and 1 g yeast extract (Burlage 1998). The medium was sterilized by autoclaving 125 mL serum bottles containing 100 mL lactate‐C for 15 min at 121°C, 15 psi. The serum bottles were made anoxic by sparging them with filter‐sterilized ultrapure nitrogen for 20 min at 10 psi. The experiments started with 2 mL of 40% frozen glycerol stocks (v/v) to reduce phenotypic drift from repetitive culturing. OA G20 cultures were grown to mid‐log phase (OD₆₀₀ = 0.13) in 100 mL lactate‐C at 30°C, 125 rpm. To remove hydrogen sulphide (H₂S), the active culture was flushed for 1 h in an exhaust hood with filter‐sterilized ultrapure nitrogen followed by centrifugation for 10 min at 10,000× g. The cell pellets were collected and cleansed twice with anoxic phosphate buffer saline (PBS, 50 mM, pH 7.2). The washed cells were then resuspended in anoxic PBS, and a 5% inoculum was utilized for further experiments. All the inoculations, cell washing and transfers were done inside an anaerobic chamber (COY Lab Products, Grass Lake, MI, USA).

2.2. Preliminary Studies

The preliminary study on the impact of Cu ions on OA G20 planktonic growth and biofilm formation on glass coupons has been previously reported by our group (Thakur et al. 2024). Variable concentrations of 5, 15, 30, 60, 80 and 100 μM of CuCl₂ were tested to conclude the harmful effects of Cu on planktonic growth where 30 μM was seen to have an inhibitory effect on the growth of OA G20. Biofilm development was also assessed across the above‐mentioned concentration ranges on two different surfaces (96‐well plates and glass coupons) by utilizing various analytical methods like OD₆₀₀, total protein quantification, crystal violet staining, scanning electron microscopy and confocal microscopic analysis (Thakur et al. 2024).

2.3. Copper Treatment

0.05 M filter‐sterilized stock solution of CuCl₂ was used to achieve the desired concentrations of Cu. The serum bottles containing 100 mL of growth medium were supplemented with 0.05 M CuCl₂ to achieve the final concentrations of 30 μM. The serum bottles with no supplemented CuCl₂ were used as a control (0 μM) in the study.

2.4. Biofilm Formation

Glass slides were used to grow OA G20 biofilm exposed to Cu stress as previously described (Thakur et al. 2024; Clark et al. 2007). The glass slides were cut in half and immersed in serum bottles containing lactate‐C medium (100 mL), and then the serum bottles were made anoxic using ultra‐pure nitrogen. The current experiment was performed in biological triplicates, and the serum bottles were supplemented with 0.05 M CuCl₂ to make a final concentration of 30 μM. The serum bottles, including control (no added Cu), were inoculated with 5% v/v seed culture inside an anaerobic chamber. The inoculated samples were placed in an incubator at 30°C, 25 rpm. Biofilm was grown for 5 days, and the biomass was extracted for proteomics analysis. Our prior study demonstrated that OA G20 biofilms reach a physiologically stable state by Day 5 when exposed to 30 μM Cu (Thakur et al. 2024). Building on our previous findings, we selected Day 5 to represent a mature biofilm state.

2.5. Protein Sample Preparation

2.5.1. Intracellular Protein Extraction

For the intracellular protein fraction, glass slides were removed and rinsed carefully with 50 mM PBS (pH 7.2). The biofilm samples were then collected by scraping the glass slides with sterile single‐use cell scrapers (Thakur et al. 2024; Clark et al. 2007). The scraped cells were further collected by centrifugation at 5000× g for 10 min and stored overnight at −80°C. The cell pellets were homogenized in B‐PER Complete Bacterial reagent (Thermo Fisher Scientific # 89822, Waltham, MA, USA) by constant pipetting and the homogenized solution was incubated at room temperature for 15 min. The cell lysate was centrifuged at 16000× g for 20 min, supernatant was collected as the intracellular protein fraction (Koo et al. 2023). Next, the supernatant was subjected to detergent removal using Pierce Detergent Removal Spin Columns (Thermo Fisher Scientific # 87777, Waltham, MA, USA) (Antharavally et al. 2011) and the purified samples were stored at −20°C until shipped for LC/MS analysis.

2.5.2. Extracellular Protein Extraction

To collect the extracellular protein fraction, the remaining media after removing the glass slides was centrifuged for 10 min at 10,000× g to collect the cell pellet. The supernatant was collected, filter‐sterilized (0.2 μm), and the extracellular proteins were concentrated using disposable Pierce Protein Concentrators PES, 3 K MWCO (Thermo Fisher Scientific, Cat # 88526, Waltham, MA, USA). After rinsing the PES membrane, 25 mL of the supernatant was centrifuged at 6000× g in a fixed‐angle rotor at 22°C until a final retentate volume of 1 mL was achieved for all the samples; centrifugation time varied between conditions due to differences in protein content (Silva et al. 2012). Concentrated samples were recovered, and total protein concentration was confirmed using Qubit, with all samples yielding a minimum of 100 μg protein. The samples were stored at −20°C until shipped for analysis.

2.5.3. Proteomic Analysis: Quantification, Trypsin Digestion and LC/MS Analysis

The final protein concentration for intracellular and extracellular fractions was measured by Qubit fluorometer using a Qubit protein kit following the manufacturer's instructions (Thermo Fisher Scientific # Q33211). The protein samples were then shipped on dry ice to Nevada Proteomics Center, Reno, Nevada, USA. After the samples were received by the Nevada Proteomics Center, a fluorescent‐based protein assay was performed for all the samples to quantify the protein content. Next, protein samples were subjected to trypsin digestion using a Thermo Scientific EasyPep Mini MS Sample prep kit (Cat #A40006) following the manufacturer's protocol. The protocol started with 100 μg of protein extracts, which were reduced and subsequently alkylated using iodoacetamide. The protein samples were then digested using a trypsin/Lys‐C protease mixture at a ratio of 1:10 (enzyme to protein). After trypsin digestion, the resulting peptides were purified using the columns provided in the EasyPep kit. The purified peptides were then resuspended in 100 μL of 0.1% formic acid in water to achieve a final concentration of 1 μg/μl for further LC/MS analysis.

The samples were analysed using an UltiMate 3000 RSLCnano system (Thermo Scientific, San Jose, CA). Before separation, the peptides were trapped on a C18 PepMap 100 trap (300 μm inner diameter × 5 mm; Thermo Scientific, San Jose, CA) for 5 min at a flow rate of 10 μL/min. Next, chromatographic separation was performed using a 50 cm uPAC C18 nano‐LC column (Pharma Fluidics, Ghent, Belgium) connected to an EasySpray source (Thermo Scientific, San Jose, CA) equipped with a 30 μm inner diameter stainless steel emitter (PepSep, Marslev, Denmark). Separation was performed at 350 nL/min using a gradient from 1% to 45% for 60 min (Solvent A 0.1% Formic Acid, Solvent B Acetonitrile, 0.1% Formic Acid). MS analysis was then conducted using Data Independent Analysis (DIA) on an Eclipse Tribrid Orbitrap mass spectrometer (Thermo Scientific, San Jose, CA) (Gillet et al. 2012; Doerr 2015).

2.6. Protein Identification and Data Analysis

The proteins were identified by analysing the data using Spectronaut software (Version 19) (Biognosys, Schlieren, Switzerland) (Midha et al. 2020). The chromatographic library was created using Spectronaut software integrated with the Pulsar database search engine, combining both DIA (Data Independent Analysis) and DDA (Data Dependent Analysis) spectral data. This hybrid library was constructed by incorporating six gas phase fractions (GPF) along with full scan DDA performed on the pooled biological samples. OA G20 protein database was downloaded from NCBI containing a total of 3219 proteins (NCBI 2005). The known contaminants database (Crap_uniprot_No_human_MRSonbeadV2) was downloaded from UniProt and incorporated into the Spectronaut analysis. For data quality control, strict identification thresholds were applied, with precursor and protein Q value cutoffs set to 0.01. Initial statistical analysis was performed within the Spectronaut software (Version 19). The detailed protocol for MS analysis and protein identification using Spectronaut is provided in File S1. The resulting files also contained many hypothetical proteins which were identified by using MOTIF Search webserver. The function of proteins explained in this study was identified utilizing an amalgamation of literature review, correlating with UniProtKB and KEGG.

2.7. Statistical Analysis

Differential abundance analysis was performed on data from three biological replicates (n = 3) per condition (30 μM Cu and control) for both intracellular and extracellular fractions. Raw peptide and protein intensities were globally normalized using the default normalization strategy in Spectronaut (Biognosys, Schlieren, Switzerland) software version 19 to account for run‐to‐run variation. Identification confidence was controlled using a false discovery rate (FDR) with Q value cutoffs of 0.01 for precursor (run and experiment levels) and protein (experiment level), and 0.05 for protein (run level). Principal component analysis (PCA) was used to assess sample clustering and identify potential outliers among biological replicates. Though some variation in clustering was observed, no replicates were excluded from statistical analysis (Figure S1). Differential abundance testing was performed using a two‐sample, two‐sided, unpaired Welch's t‐test at the protein group level, with multiple testing correction applied via the Storey method at the experiment level, generating Q values. Fold changes are expressed as log2 ratios of average biological replicates, calculated as Cu‐treated relative to control (log2FC = Cu/control). Proteins and peptides were considered significantly differentially expressed at p value < 0.05 and |log2FC| ≥ 1. All statistical analyses were performed in Spectronaut v19, and data visualization, including volcano plots, scatter plots, bubble plots and Venn diagram, were generated using custom Python scripts (File S2) and Venny 2.1 software (Oliveros 2007).

3. Results

3.1. Comparative Proteomic Response of OA G20 Biofilm at High Cu Exposure

Our previous work demonstrated that 30 μM Cu inhibited planktonic growth while significantly enhancing OA G20 biofilm formation (Thakur et al. 2024); therefore, proteomic response of 5‐day OA G20 biofilms exposed to 30 μM Cu was assessed in comparison to control (0 μM Cu). The MS/MS spectrum depicted optimal intensity and quality for further analysis (Figure S2a–l). A total of 1114 (intracellular) and 931 (extracellular) proteins with FDR of 0.01 were identified. Figure 1 highlights the distribution of unique and shared proteins between intracellular and extracellular groups, presenting statistically significant (|log2FC| > 1) up‐ and downregulated proteins in each fraction. Proteins with statistically significant differences (p value < 0.05) were determined based on a pairwise comparison of the OA G20 control biofilm (0 μM) with OA G20 biofilm grown in 30 μM Cu. Proteins with differential abundance (p value < 0.05) were further filtered based on the average log2 fold change (FC) ratio between 30 and 0 μM Cu (Figure 2). There were 492 distinct proteins with greater than 2‐fold change (|log2FC| > 1) in 30 μM Cu relative to control (0 μM Cu) where a total of 382 distinct proteins were identified with 1 < |log2FC| < 2, and 110 proteins showed significant modulation with |log2FC| > 2. Differentially abundant proteins identified from intracellular and extracellular fractions were further analysed to understand the specific mechanisms and pathways impacted by exposure to 30 μM Cu (File S3). Potential functions of these proteins include sulphur metabolism, response to environmental stress, development of biofilms, metal homeostasis and proteins with unknown functions. Detailed descriptions of these proteins are presented in the section below.

FIGURE 1.

Venn diagram depicting the number of significantly differentially abundant proteins (n = 3) in the intracellular and extracellular fractions of OA G20 under 30 μM Cu treatment relative to control. Proteins were considered significant at p value < 0.05 and |log2FC| ≥ 1 (unpaired t‐test).

FIGURE 2.

Volcano plot representing the proteome analysis of proteins in (a) Intracellular fractions extracted from the OA G20 biofilm samples grown on glass slides and (b) Extracellular fractions isolated from cell‐free supernatant of OA G20 biofilm samples (n = 3). Points highlighted in red represent proteins with statistical significance (unpaired t‐test) and |log2FC| > 1 when OA G20 cultures were supplemented with 30 μM Cu ion concentrations relative to control (no Cu). Dotted blue lines show the applied significance thresholds of p value = 0.05. Dotted green lines represent the applied threshold for significantly regulated proteins of |log2FC| > 1. Information about these proteins is presented in File S3.

3.2. Impact of High Cu Exposure on Intracellular and Extracellular Protein Abundance

Categorization of differentially expressed proteins (DEPs) as intracellular and extracellular provides insights into the impact of Cu exposure on cellular metabolism and its impact on secreted proteins governing biofilm formation (Bamford et al. 2023). In total, 251 distinct intracellular proteins showed |log2FC| > 1, and 241 extracellular proteins were observed with |log2FC| > 1. File S4 lists all extracellular and intracellular proteins with at least a 2‐fold change (|log2FC| > 1) identified in OA G20 samples exposed to 30 μM Cu relative to control (0 μM Cu). Among the 251 intracellular and 241 extracellular proteins, 18.32% and 26.55% respectively exhibited at least a 4‐fold change (|log2FC| ≥ 2) in abundance. Filamentous temperature‐sensitive mutant Z (FtsZ) protein showed the highest relative abundance (65‐fold change) among all extracellular proteins. FtsZ is part of prokaryotic cell division proteins, and previous studies have implicated its role in increased biofilm formation (Cooper et al. 2023; Han et al. 2021). However, FtsZ is primarily known as a cytoplasmic protein involved in cell division; its high relative abundance in the extracellular fraction may reflect cell lysis or membrane stress rather than active secretion. This observation is discussed in detail in Section 4.5. The most upregulated intracellular protein was Zinc resistance‐associated protein (ZraP) with log2FC of 3.29. A high abundance of ZraP in 30 μM Cu implicates its role in Cu stress tolerance as indicated in previous studies (Tripathi et al. 2022; Petit‐Härtlein et al. 2015). Table 1 shows the top 10 intracellular and extracellular proteins with the largest |log2FC| in 30 μM Cu relative to control. These proteins were found to be involved in various biological processes, including sulphur metabolism, energy metabolism, stress response, metal homeostasis and transport, biofilm formation and regulation, electron transport and hypothetical proteins (unknown function). Details of these proteins are discussed in subsequent sections.

TABLE 1.

Top 10 differentially up‐ and down‐regulated proteins with significant fold changes in both intracellular and extracellular fractions.

Intracellular (upregulated)			Extracellular (upregulated)
Protein ID	Protein description	Average log2FC	Protein ID	Protein description	Average log2FC
Dde_2819	Zinc resistance‐associated protein ZraP	3.295	Dde_1047	Cell division protein FtsZ	6.023
Dde_0785	NADPH‐dependent FMN reductase	2.988	Dde_2058	Histone family protein DNA‐binding protein	3.995
Dde_0057	Dihydroorotate dehydrogenase	2.738	Dde_3213	Histone family protein DNA‐binding protein	2.884
Dde_0399	Acetolactate synthase	2.566	Dde_2287	NUDIX hydrolase	2.668
Dde_3091	Heat shock protein Hsp20	2.396	Dde_0573	Carboxynorspermidine/carboxyspermidine decarboxylase	2.305
Dde_1429	ABC‐type transporter, periplasmic subunit family 3	2.294	Dde_3129	Phosphate butyryltransferase	2.287
Dde_1979	Methylglyoxal synthase (MGS)	2.140	Dde_3278	Microcompartments protein	2.147
Dde_0187	Flavin reductase domain protein FMN‐binding protein	2.054	Dde_0677	TorD‐like chaperone	2.130
Dde_0126	MerR family transcriptional regulator	1.975	Dde_0125	Histone family protein DNA‐binding protein	2.095
Dde_2930	dTDP‐4‐dehydrorhamnose 3,5‐epimerase	1.837	Dde_3601	Amphi‐Trp domain‐containing protein	2.007

Intracellular (downregulated)			Extracellular (downregulated)
Protein ID	Predicted function	Average log2FC	Protein ID	Predicted function	Average log2FC
Dde_1538	MotA/TolQ/ExbB proton channel	−3.760	Dde_3244	Lactate utilization protein B/C	−3.760
Dde_1818	Protein translocase subunit SecD	−3.563	Dde_0108	Type VI secretion system spike protein VgrG3‐like C‐terminal domain‐containing protein	−3.546
Dde_2298	Fe (3+)‐transporting ATPase	−3.305	Dde_1035	Cell division protein FtsL	−3.452
Dde_3641	Sulphate transporter	−3.005	Dde_2436	Riboflavin biosynthesis protein RibBA	−3.229
Dde_3061	M18 family aminopeptidase	−2.975	Dde_3367	Peptidase M15A	−3.225
Dde_2144	Lipoprotein	−2.910	Dde_2958	Flagellar basal body rod protein	−3.137
Dde_2598	Ribonuclease R (RNase R)	−2.878	Dde_1839	Lipoprotein	−3.100
Dde_1031	Metal dependent phosphohydrolase	−2.790	Dde_1713	Flagellar hook‐length control protein FliK	−3.075
Dde_1665	Methyl‐accepting chemotaxis sensory transducer with Cache sensor	−2.724	Dde_2274	Periplasmic (Tat), binds 2 (4Fe‐4S)	−3.056
Dde_2256	Large ribosomal subunit protein uL4 (50S ribosomal protein L4)	−2.664	Dde_2623	Outer membrane protein	−3.051

3.3. Gene Ontology Enrichment Analysis

3.3.1. Functional Enrichment of Intracellular DEPs

GO analysis was performed for intracellular upregulated and downregulated DEPs. The GO analysis categorized these proteins into three main functional categories: molecular function (MF), cellular component (CC) and biological process (BP). The significantly enriched GO terms (p value < 0.05) for intracellular DEPs are shown in Figure 3. Intracellular up‐ and down‐regulated DEPs revealed a total of 81 GO terms, constituting 41 MF, 31 BP and 9 CC terms (File S5). The top three most enriched GO terms were selected for each major category. For the MF category, the number of DEPs enriched in each GO term was as follows: ATP binding (GO:0005524, 5 upregulated and 27 downregulated proteins), oxidoreductase activity (GO:0016491, 8 upregulated and 1 downregulated proteins), and hydrolase activity (GO:0016787, 3 upregulated and 2 downregulated proteins). The enrichment of GO:0005524 with downregulated DEPs indicates the bacteria is conserving energy for metabolic reactions, various synthesis processes and heavy metal ion translocation. The upregulated proteins included in GO:0005524 and GO:0016491 are involved in the reduction process of heavy metal ions (Li et al. 2021). The proteins related to GO:0016787 are involved in heavy metal‐related transport activity across biofilm (Wang et al. 2020). In the BP category, GO terms related to cell wall organization (GO:0071555, 2 upregulated and 3 downregulated proteins), isoleucine biosynthetic process (GO:00090971, 2 upregulated and 1 downregulated proteins) and cell division (GO:0051301, 2 downregulated proteins) were enriched. The enrichment of proteins associated with GO:0071555 and GO:0051301 terms suggests bacterial adaptation strategies under stress by regulating cell division and cell wall biosynthesis (Tripathi et al. 2022; Triola et al. 2009). DEPs in the CCs functional category followed the order: plasma membrane (GO:0005886, 3 upregulated and 21 downregulated proteins), membrane (GO:0016020, 5 upregulated and 10 downregulated proteins), ribonucleoprotein complex (GO:1990904, 1 upregulated and 7 downregulated proteins), indicating the subcellular location of these DEPs.

FIGURE 3.

Gene ontology functional analysis of DEPs (n = 3, p value < 0.05, |log2FC| > 1, unpaired t‐test) in intracellular fractions of OA G20 under 30 μM Cu treatment relative to control. (a) GO molecular function (GO_MF), (b) GO biological process (GO_BP) and (c) GO cellular component (GO_CC) classifications. The bubble plot shows enriched GO functional categories with their respective −log10 (p value) and GO terms, with bubble size representing the number of proteins per GO category.

3.3.2. Functional Enrichment for Extracellular DEPs

The GO category enrichment was also performed for extracellular DEPs (p value < 0.05), shown in Figure 4. Extracellular up‐ and downregulated DEPs revealed a total of 90 functional terms, constituting 49 MFs, 9 CCs and 32 BPs (File S6). The top three enriched GO terms were selected for each GO category. In the context of the MF category, metal ion binding (GO:0046872, 5 upregulated and 15 downregulated proteins) was the most enriched followed by magnesium ion binding (GO:0000287, 1 upregulated and 5 downregulated proteins) and GTP‐binding (GO:0005525, 1 upregulated and 3 downregulated proteins). The presence of these metal ion binding terms suggests the role of the related proteins in ionic bridging within the EPS matrix, enhancing cell aggregation and promoting biofilm formation (Chen et al. 2019). The GTP‐binding GO term includes proteins that play central roles in regulating bacterial cell division and amino acid synthesis (Hesketh et al. 2015; Rojas et al. 2017). GO terms related to cell division (GO:0051301, 4 downregulated proteins), dTDP‐rhamnose biosynthetic process (GO:0019305, 2 upregulated proteins) and bacteriocin transport (GO:0043213, 2 downregulated proteins) were frequently observed in the BP category. Interestingly, the DEPs associated with GO:0019305 play a key role in biofilm formation and polysaccharide biosynthesis in bacteria (Tsukioka et al. 1997; Michael et al. 2016). Proteins related to GO:0043213 are involved in efflux systems creating passage across the cell membrane and transporting small solutes outside the bacteria (Simons et al. 2020). Further, cytoplasm (GO:0005737, 8 upregulated and 23 downregulated proteins) and membrane (GO:0016020, 1 upregulated and 10 downregulated proteins) were significantly enriched in the CCs category.

FIGURE 4.

Gene ontology functional analysis of DEPs (n = 3, p value < 0.05, |log2FC| > 1, unpaired t‐test) in extracellular fractions of OA G20 under 30 μM Cu treatment relative to control. (a) GO molecular function (GO_MF), (b) GO biological process (GO_BP) and (c) GO cellular component (GO_CC) classifications. The bubble plot shows enriched GO functional categories with their respective −log10 (p value) and GO terms, with bubble size representing the number of proteins per GO category.

3.4. Prediction of Hypothetical Proteins

Several hypothetical proteins depicted significant changes in expression under Cu stress conditions. Of all the intracellular and extracellular proteins, approximately 4.8% intracellular were hypothetical (54/1114 proteins), and 8.4% extracellular were hypothetical (79/931). A total of 133 hypothetical protein hits were identified across both fractions (54 intracellular and 79 extracellular) (File S7). Of these, 27 hypothetical proteins were detected as differentially regulated in both the intracellular and extracellular fractions, representing the same protein in each fraction, whereas the remaining 79 were fraction‐specific (27 unique to the intracellular fraction and 52 unique to the extracellular fraction). The violin plot in Figure 5 shows the average log2FC values for hypothetical extracellular and intracellular proteins, along with their respective p values. The peaks of the plot indicate regions of higher density indicating hypothetical extracellular proteins were predominantly downregulated (75.9%), whereas hypothetical intracellular proteins were mostly neutral or upregulated (57.4%) (Figure 5). Annotation of hypothetical proteins is essential for describing their MFs and potential roles within a microorganism. Therefore, the MOTIF Search webserver was utilized to predict the function of these hypothetical proteins. Table 2 presents the annotation results of the five most differentially expressed hypothetical proteins, which might contribute to broadening our understanding of these proteins in bacterial stress response. It is important to note that of the 133 hypothetical proteins, only 47 proteins were identified using MOTIF Search webserver with a cutoff value of 1 × 10⁻² as a threshold for significance. The predicted function of these hypothetical proteins is presented in File S7.

FIGURE 5.

Violin plot comparing the distribution of average log2FC values for hypothetical proteins of unknown function in the extracellular (79 proteins) and intracellular (54 proteins) fractions of OA G20 under 30 μM Cu treatment relative to control (n = 3, unpaired t‐test). Each point represents one protein, coloured by −log10 (p value); the dashed red line on the colour scale indicates the p value = 0.05 significance threshold.

TABLE 2.

List of upregulated and downregulated hypothetical proteins predicted by MOTIF Search online tool.

Intracellular (upregulated)			Extracellular (upregulated)
Protein ID	Predicted function	Average log2FC	Protein ID	Predicted function	Average log2FC
Dde_2573	Prokaryotic membrane lipoprotein lipid attachment site profile	1.827	Dde_2755	Post‐translational modification, protein turnover, chaperones	1.805
Dde_1678	Prokaryotic membrane lipoprotein lipid attachment site profile	1.542	Dde_1389	Prokaryotic membrane lipoprotein lipid attachment site profile	1.019
Dde_0344	Cell wall/membrane/envelope biogenesis	1.502	Dde_1544	Type III secretion system, cytoplasmic E component of needle	0.880
Dde_1466	Prokaryotic membrane lipoprotein lipid attachment site profile	0.955	Dde_2819	CpxP component of the bacterial Cpx‐two‐component system and related proteins	0.979
Dde_1544	Type III secretion system, cytoplasmic E component of needle	0.9339

Intracellular (downregulated)			Extracellular (downregulated)
Protein ID	Predicted function	Average log2FC	Protein ID	Predicted function	Average log2FC
Dde_2144	Prokaryotic membrane lipoprotein lipid attachment site profile.	−2.910	Dde_2706	MotE, Flagellar motility protein MotE, a chaperone for MotC folding [Cell motility]	−3.788
Dde_0287	Outer membrane protein chaperone/metalloprotease	−1.019	Dde_0108	Type VI secretion system spike protein VgrG3‐like, C‐terminal	−3.545
Dde_2754	Lipopolysaccharide‐assembly	−0.123	Dde_1035	FtsL2, Cell division protein FtsL [Cell cycle control, cell division, chromosome partitioning]	−3.45
Dde_3707	Periplasmic component TolB of the Tol biopolymer transport system (Intracellular trafficking, secretion and vesicular transport)	−0.042	Dde_1839	Prokaryotic membrane lipoprotein lipid attachment site profile	−3.100
			Dde_2622	ABC‐type uncharacterized transport system, periplasmic component [General function prediction only]	−2.191

4. Discussion

4.1. Proteins Related to Stress Response

Cu toxicity mechanisms in bacteria involve the production of ROS, depletion of glutathione and disruption of catalytic iron–sulphur clusters (Raya et al. 2022). Cu ions induce oxidative stress by producing ROS, which can significantly damage proteins, nucleic acids and lipids (Thakur et al. 2024; Vaishampayan and Grohmann 2021). Bacteria overcome Cu toxicity by deploying various stress responses that help regulate Cu by various processes, for example, Cu uptake, detoxification, removal and accumulation, which are critical for bacterial survival (Solioz and Solioz 2018). Bacteria defend themselves from oxidative stress using flavin reductase (FRs), NADPH‐dependent FMN reductase, and NADPH dehydrogenase (Quinones) as antioxidative systems to maintain cellular redox homeostasis (Corpas and Barroso 2014).

In this study, FRs (Dde_0187), NADPH‐dependent FMN reductase (Dde_0785), and NADPH dehydrogenase (Quinones) (Dde_1618) were upregulated > 3‐fold, > 2‐fold, and > 1‐fold, respectively, in biofilm samples (File S8). FRs are involved in the reduction process of free flavins, NADH, NADPH, FMN, riboflavin and FAD. The regulation of NADPH‐dependent FMN reductase plays a key role in cell growth, oxidative defence (Sedláček and Kučera 2019) and metal stress response (Sepúlveda Cisternas et al. 2018). Additionally, the positive regulation of FRs is previously reported to be involved in cell adhesion and oxidative stress response in Streptococcus pneumoniae (Morozov et al. 2018). Other proteins upregulated in this study were nitroreductase and thioredoxin reductase. Nitroreductase is a flavoprotein that can reduce flavins and nitroaromatic compounds using reductants like NADH or NADPH (Mermod et al. 2010). These reduced flavins serve as cofactors for several enzymes, including the luciferase enzyme from Vibrio harveyi (Lei and Tu 1998), and have been documented to facilitate the reduction of uranium (VI) in OA G20, thereby contributing to metal homeostasis (Sepúlveda Cisternas et al. 2018).

In our study, proteins related to nitroreductase (Dde_1353, log2FC = 1.88 and Dde_2524, log2FC = 1.60) were significantly upregulated. This positive regulation of nitroreductase in the presence of Cu corroborates with the study on Lactococcus lactis . The nitroreductase of L. lactis , CinD, has an increased expression in the presence of Cu, allowing the bacteria to reduce and detoxify compounds that caused oxidative stress (Mermod et al. 2010).

Furthermore, the upregulation of thioredoxin reductase proteins (Dde_2066, Dde_2067, Dde_2151) was observed in Cu‐biofilm samples relative to the control (File S8). Similar findings were reported by Jawaharraj et al., where upregulation of stress‐responsive genes was observed when OA G20 biofilm was grown on Cu surfaces (Jawaharraj et al. 2023). This study also observed the downregulation of the following proteins: Quinone‐interacting membrane‐bound oxidoreductase (Qmo), Pyruvate: ferredoxin oxidoreductase (PFOR), Aldehyde dehydrogenase (FAD‐independent), and 4‐hydroxy‐tetrahydrodipicolinate reductase (HTPA reductase). In Desulfovibrio species, Qmo, a transmembrane protein, is known to be involved in respiratory electron transfer chain and energy conservation (Kuehl et al. 2014; Pires et al. 2003). Qmo (Dde_1113) was found to be negatively regulated (log2FC = −1.088) in comparison to the control. This downregulation can be interpreted as an attempt by OA G20 to conserve energy for other vital metabolic processes. Similarly, Pyruvate: ferredoxin oxidoreductase (PFOR, Dde_3237) was downregulated with log2FC = −1.59. In Thermococcus kodakarensis , pyruvate oxidoreductase reduces ferredoxins, which transfer electrons to various acceptors, including proteins involved in stress response (Burkhart et al. 2019). Similar findings were observed in the anaerobic protozoan Giardia lamblia where a negative regulation of the PFOR was found to be associated with metronidazole drug resistance (Leitsch et al. 2011). The differential expression of all these proteins suggests high Cu concentrations trigger a stress response to protect the bacteria from oxidative stress by regulating protein expression.

4.2. Proteins Involved in Efflux or Transporter Proteins

The bacterial transport system consists of a diverse class of transporter proteins, including ATP‐Binding Cassette (ABC), Resistance‐Nodulation division (RND) transporters, and efflux pump proteins. The transporter proteins play a crucial role in various processes, including signal and energy transduction, drug and antibiotic resistance, physiological and developmental processes, and bacterial pathogenesis. These proteins participate in the translocation of ligands, solutes, cations, amino acids, anions, sugars, proteins, electrons, water and material for biofilm formation (Mishra et al. 2014; Higgins 1992; Lee et al. 2018). The tripartite efflux system, a group of multidrug efflux pumps that use the Type I secretion system, plays a critical role in Gram‐negative bacteria by actively expelling drugs or heavy metal ions outside the bacterial cells. This system consists of outer membrane factors (OMFs) of the TolC family, periplasmic adaptor proteins (PAPs), and inner membrane transporters (RND and ABC) (Pos 2024; Symmons et al. 2015). The detailed role of these systems in bacterial adaptation and survival under stress has been explained in the following sections.

4.2.1. Upregulation of ABC Transporters

The superfamily of ABC‐type transporters consists of membrane proteins that function as both exporters and importers. ABC‐importers are characterized by the presence of a periplasmic ligand‐binding domain, which is vital for ligand acquisition and translocation (Rees et al. 2009). The importer proteins are linked with nutrition acquisition and virulence (Cui and Davidson 2011) whereas the ABC‐exporters take part in drug efflux and cellular detoxification, influencing survival and drug‐tolerant strain development (Cassio Barreto de Oliveira and Balan 2020). This study showed upregulation (approximate fold change ≥ 1) in various ABC‐type transporter systems (File S9). The major upregulated proteins involved in the ABC transport systems were ABC‐type glycine betaine transport, periplasmic subunit (Dde_3306, intracellular, log2FC = 1.31, p value = 0.00023), zinc ABC transporter (Dde_2208, intracellular, log2FC = 0.59, p value = 0.015) and ABC transporter periplasmic substrate‐binding proteins (PSBPs) (Dde_0234, extracellular, log2FC = 0.41, p value = 0.00068) (File S9).

The ABC‐type glycine betaine transport proteins are involved in enhanced growth, surface attachment and biofilm formation of Vibrio cholerae (Kapfhammer et al. 2005). The ABC‐transporter PSBP, NikA, in E. coli was reported to obtain Ni(II) ions under anoxic conditions for utilization in hydrogenase enzymes (Maqbool et al. 2015). Whereas the ABC‐transporter PSBP, DppA1, of Pseudomonas aeruginosa coordinates the uptake and transport of dipeptides (nutrients), repressing phage production and promoting biofilm formation (Lee et al. 2018). The upregulation of the zinc ABC transporter (ZnuA, ZnuB) indicates low zinc availability. In bacterial cells, zinc serves as an essential cofactor for numerous proteins. When bacteria encounter environments with limited zinc, they respond by modulating the expression of ZnuABC transporters (Gabbianelli et al. 2011). A previous study on E. coli has demonstrated that ΔznuA and ΔznuB mutants have significantly reduced biofilms compared to the wild type, emphasizing the importance of ZnuAB regulation in biofilm development (Quan et al. 2020).

4.2.2. Regulation of Periplasmic Adaptor and Outer Membrane Proteins

Periplasmic adaptor proteins (PAPs) act as a linker between the inner and outer membrane (OM) channels, allowing efflux and transport of toxic molecules. They also play a significant role in ligand recognition, selection and control of energy flow (Symmons et al. 2015). In this study, differential regulation of RND transporter PAPs was observed in both intracellular and extracellular fractions. The protein related to PAPs, Dde_0402 (log2FC = 0.94) was moderately upregulated in the intracellular fraction, whereas in the extracellular fraction Dde_0965 and Dde_0962 were significantly downregulated (log2FC = −2.42 and log2FC = −1.41, respectively) compared to the control. These results are in agreement with studies in P. aeruginosa , where clinical isolates overexpress the RND‐transporter MexXY–OprM under aminoglycoside exposure, relative to wild‐type strains with a functional mexZ regulator, thereby conferring antibiotic resistance (Colclough et al. 2020). In addition, previous studies on mutants lacking efflux pumps in E. coli and Salmonella enterica reported a reduction in cell adhesion supporting the role of RND efflux pumps in biofilm formation (Gaurav et al. 2023). The TolC proteins (Dde_3627 and Dde_0961) and proteins related to the Type I secretion system (Dde_0594, Dde_1419 and Dde_1416) were also downregulated in the presence of 30 μM Cu ions in the extracellular and intracellular fractions, respectively (File S9).

4.3. Lipopolysaccharide and Lipid Transport

The outer membrane of Gram‐negative bacteria is composed of an inner and an outer leaflet, containing phospholipids and lipopolysaccharides (LPS), respectively. These components within the outer membrane are known to elicit a complete adaptive response in E. coli and play a role in structural integrity, cell morphology, bacterial adhesion and biofilm formation (Emiola et al. 2016; Rowlett et al. 2017). The asymmetry of the outer membrane is maintained by the Mla (maintenance of OM lipid asymmetry) intermembrane transport system, which transports phospholipids from the outer leaflet to the inner leaflet (Wotherspoon et al. 2024). The Mla proteins have been shown to play important roles in bacterial motility, cell shape and biofilm formation (Kaur and Mingeot‐Leclercq 2024). The effect of Mla protein modulation can vary in different strains, where its regulation or complete inactivation can increase biofilm formation, as seen in Bordetella pertussis (de Jonge et al. 2022). In this study, a decrease in expression was observed for the Mla protein, MlaD (Dde_2299, log2FC = −0.79). This downregulation can be attributed to reduced motility exhibited by OA G20 when transitioning from planktonic to biofilm state. In addition, Lpt (an LPS transport system) is responsible for the transport of LPS, which confers structural integrity and resistance against environmental stress (Dajka et al. 2024). Our study observed downregulation in LptB (Dde_1770, log2FC = −1.06). This downregulation in LptB can activate other stress‐responsive pathways, like the activation of Rcs (Regulation of capsule synthesis) system, which has been previously observed in Yersinia pestis to regulate biofilm formation and exopolysaccharide synthesis (Meng et al. 2021). Therefore, the change in cell morphology and increase in biofilm formation in 30 μM Cu samples may be linked to the regulation of Mla and LptB proteins.

4.4. Modulation of Flagellar Assembly and Motility Related Proteins

Bacteria sense their surroundings by utilizing rotating helical structures known as flagella to swim towards favourable conditions. The flagellum serves as a critical cellular structure that enables bacterial motility and chemotaxis. This organelle is composed of two primary structural elements: the basal body rings and the axial structure (Sowa and Berry 2008; Liu et al. 2020). The basal body forms the rotary motor, including a stator complex composed of MotA and MotB proteins, and four main ring structures (L‐ring, P‐ring, MS‐ring and C‐ring). Whereas the tubular axial structure consists of a filament (a long, thin helical propeller made of flagellin proteins, FliC), the hook (a short, curved universal joint composed of FlgE proteins), and the rod (a drive shaft connecting the rotor rings to the hook, made of FlgB, FlgC, FlgF and FlgG proteins) (Imada 2018). Moreover, flagellation and motility have been reported to play a crucial role in multiple stages of biofilm formation by facilitating cell attachment on biotic and abiotic surfaces (Vatanyoopaisarn et al. 2000).

Our results show that more than 20 DEPs related to flagellar assembly and motility were regulated in both intracellular and extracellular fractions (File S10). The most upregulated proteins in the intracellular fraction corresponded to a MotB‐domain containing protein (Dde_1716, log2FC = 1.28 and Dde_1539, log2FC = 1.18). Although in the extracellular fraction, a significant downregulation of proteins related to flagellar hook‐length FliK (Dde_1713, log2FC = −3.07), FliE (Dde_0354, log2FC = −2.01), and FlgD (Dde_1712, log2FC = −2.00) was observed. Other proteins related to flagellar assembly, including FlgE (Dde_1711), Flagellar P‐ring protein FlgI (Dde_3155, |log2FC| > 1) and Flagellin FliC (Dde_1709, |log2FC| > 1) were upregulated in intracellular and downregulated in extracellular fractions, respectively.

Generally, biofilm formation is characterized by the downregulation of flagellum‐dependent motility (Pisithkul et al. 2019; Belas 2013). Interestingly, our study found an upregulation and downregulation of flagellar proteins in the intracellular and extracellular fractions, respectively. These results are in corroboration with previous biofilm studies on OA G20 (Thakur et al. 2024) and E. coli (Yang et al. 2023) where upregulation of flagella and motility genes was observed under stress. Additionally, differential expressions of these proteins can be attributed to cells trying to move away from the toxic Cu environment to a safer environment by swimming towards the glass surface. Another reason for the upregulation of flagellar proteins can be linked to the cells transitioning from the sessile to the planktonic state, allowing the bacteria to localize and form new biofilms under favourable conditions (McDougald et al. 2012). In addition, proteomics data revealed strong upregulation of protein Type IV pilus (T4P) assembly, PilZ (Dde_1460) with fold change > 2 in the intracellular protein fraction. PilZ domain‐containing proteins are key regulators of T4P assembly and function by interacting with cyclic‐di‐GMP, a key secondary messenger influencing various processes like cell motility and biofilm formation (Wang et al. 2024; Kuzmich et al. 2021; Hendrix et al. 2024).

4.5. Cell Morphology

Changes in cell morphology like an increase in cell size under stressful conditions have been previously observed for various bacteria (Chen et al. 2009; Rajdeep Chakravarty et al. 2007). In our previous studies with OA G20, SEM analysis revealed similar results where elongated cells were seen after exposure to Cu ions (Thakur et al. 2024; Tripathi et al. 2022). The changes in cell morphology have been described as a defence mechanism adapted by bacteria to survive under stress (Rajdeep Chakravarty et al. 2007; Oh et al. 2015; Nepple et al. 1999). Our current study noted significant regulation of proteins involved in cell division, cell shape, and elongation processes. Rod‐shaped bacterial cells maintain their cell shape and division by regulating proteins MreB and FtsZ, respectively. In this study, the FtsZ protein was the most upregulated in the extracellular fraction with log2FC = 6.02, whereas MreB (Dde_0996) was upregulated (log2FC = 1.06) in the intracellular fraction. MreB acts as the elongation factor which supports the elongated shape of the bacterial cell, and FtsZ, on the other hand, controls the spatial and temporal modulation of cell division. These proteins play a major role in biofilm formation (Charles 2019). The positive regulation of MreB (> 2 fold) is in agreement with a transcriptomics study of P. aeruginosa biofilms under oxidative stress (Maybin et al. 2023), suggesting the bacteria is attempting to repair the cell envelope and maintain biofilm architecture (Maybin et al. 2023; Jeckel et al. 2022).

Additionally, the upregulation of the protein FtsZ is in contradiction with our previous RT‐qPCR expression studies on OA G20 biofilm where the downregulation of ftsZ (Dde_1047) was observed under Cu stress. Genetic studies on the deletion of these two proteins have shown disruption in cell growth and biofilm formation (Charles 2019; Pande et al. 2022; Maharjan et al. 2024). It is also important to note that FtsZ is primarily known as an intracellular protein crucial for cell division. The unexpected upregulation of FtsZ in the extracellular fraction requires further investigation to understand whether this observation stems from cell lysis, the presence of a unique secretion system, or a broader stress response to metal ions. In the absence of direct experimental validation, FtsZ should not be interpreted as a confirmed extracellular protein at this stage and may represent cytoplasmic contamination resulting from copper‐induced membrane stress. The precise mechanism underlying the extracellular presence of FtsZ in OA G20 under copper stress remains to be elucidated. Other DEPs influencing cell shape and elongation are listed in File S11.

4.6. Two‐Component System

Two‐component systems (TCSs) assist bacteria in sensing and responding to environmental changes (Liu et al. 2019). TCSs are used in multiple signal transduction systems, such as chemotaxis, quorum sensing (QS), cell cycle regulation and nitrogen regulation. TCSs primarily consist of two proteins: a stimuli‐sensing histidine kinase and a response regulator that elicits an appropriate cellular response (Mascher et al. 2006). Differential regulation of signal transduction systems is one of the dominant modes used by bacteria to sense and respond to several environmental cues, including factors that influence and regulate biofilm formation (Liu et al. 2019). Understanding the differential regulation of proteins involved in TCSs can aid in deciphering the mechanism of biofilm formation in OA G20. Some important TCS mechanisms used by OA G20 in this study are discussed in the following sections.

4.6.1. Chemotaxis

Chemotaxis is a cell‐signalling process by which bacterial cells navigate their environment along a chemical gradient. This movement aids bacteria in finding the optimal conditions for survival and growth (Keegstra et al. 2022). The chemotaxis system in bacteria consists of transmembrane chemoreceptors, such as methyl‐accepting chemotaxis proteins (MCPs), and signal transducing Che proteins, such as CheA, CheW, CheB and CheR (Wang et al. 2012). In this study, CheW was upregulated with fold change of greater than 2 (log2FC = 1.4). CheW is part of the two‐component system regulating bacterial chemotaxis (Griswold et al. 2002). Studies have reported that the core chemotaxis genes CheVAWY, which include CheW, influence flagellar rotation that initiates biofilm growth (Reuter et al. 2020). CheW acts as an adaptor in association with the MCP and histidine kinase (File S12). These proteins sense environmental stress that initiates a phosphorylation cascade, leading to a change in flagellar motility and subsequent biofilm formation (Alexander et al. 2010).

4.6.2. Nitrogen Regulatory NtrC

NtrC family refers to a group of TCS regulatory proteins that play a critical role in regulating nitrogen metabolism in bacteria. NtrC family primarily consists of a sensor histidine kinase protein that controls the phosphorylation state of a DNA‐binding response regulator protein. Phosphorylation of this response regulator depends on intracellular nitrogen and carbon levels (Yang et al. 2021). The phosphorylated DNA‐binding response regulator activates transcription of multiple genes involved in various physiological processes, such as biofilm formation and stress tolerance (Liu et al. 2023). The regulation of nitrogen metabolism affects the activity of an important enzyme, glutamine synthetase. Glutamine synthetase catalyses the synthesis of glutamine from glutamate and ammonium as a nitrogen source (Kumada et al. 1993). The abundance and activity of glutamine synthetase are primarily regulated by GlnB, a member of the PII regulatory protein family. In nitrogen‐deficient environments, GlnB becomes uridylylated, which then deadenylates GlnA to generate nonadenylylated GlnA, the active form of glutamine synthetase. The upregulation of Nitrogen regulatory protein PII (GlnB) in this study (Dde_2310, log2FC = 1.29) indicates the cells are under nitrogen starvation conditions (Liu et al. 2024). Though further studies are required to irrefutably conclude nitrogen limiting conditions, previous studies have shown that nitrogen regulator proteins, such as GlnB, activate the glutamine biosynthesis pathway. Previous studies have shown that inactivation of glutamine synthetase leads to arrest of biofilm formation (Liu et al. 2024; Rodionova et al. 2018) due to decrease in expression of genes responsible for exopolysaccharide and amyloid fibres (AF) secretion (Kimura and Kobayashi 2020). Exopolysaccharide helps maintain the biofilm matrix, and AF provides structural integrity to the biofilm (Romero et al. 2010; Singh et al. 2021).

4.6.3. Quorum Sensing

QS is a mode of bacterial communication that utilizes signalling molecules called autoinducers, which regulate collective gene expression in response to environmental stress (Windsor 2020; García‐Contreras et al. 2015). QS allows bacteria to coordinate and execute various functions, such as sporulation, virulence, oxidative stress response and biofilm formation. Among the three major classes of QS signalling molecules (Auto Inducer 1 (AI‐1), AI‐2 and AI‐3), AI‐1 (acyl homoserine lactone [AHL]) is the predominant molecule in OA G20 (Zhou et al. 2020). AHLs are synthesized by AI synthase LuxI homologues in the cytoplasm, which are secreted out through ABC transporters (Cai and Zhang 2024; Papenfort and Bassler 2016). Though an AHL synthase was not observed in our dataset, it might be one of the uncharacterized proteins. Based on a previous in silico study from our lab conducted on Desulfovibrio vulgaris (Tripathi et al. 2023), it is certain that an AHL synthase homologue is present in OA G20. Secreted AHLs trigger QS‐dependent communication by directly binding to LuxR homologue. DctP (Extracellular solute binding protein) was regulated > 2‐fold indicating its potential role in stress tolerance and biofilm formation. DctP, a LuxR family protein, impacts swarming motility, cell adhesion and biofilm formation. Deletion of dctP in a previous study significantly decreased biofilm formation in the Gram‐negative Vibrio alginolyticus (Zhang et al. 2022). Other DEPs involved in two‐component system are listed in File S11.

4.7. Hypothetical Proteins

The significant changes in the expression of hypothetical proteins indicate that some important components of OA G20 Cu stress tolerance utilize yet unknown mechanisms. The highest upregulated hypothetical intracellular and extracellular proteins had > 3‐fold change in expression (File S6) indicating that the mechanism of Cu stress and subsequent biofilm formation might be distinct in OA G20. Some of the significantly regulated hypothetical proteins (|log2FC| > 1) predicted by MOTIFSearch webserver were related to prokaryotic membrane lipoprotein, cell and flagellar motility, Type VI secretion system (T6SS), and ABC transport system (Table 2). One of the hypothetical proteins identified was the spike protein VgrG3 (Dde_0108, log2FC = −3.5), which is an essential component of T6SS. It has been previously reported that VgrG can regulate biofilm formation, growth, and resistance to environmental stresses (Sha et al. 2013; Yang et al. 2018). The other protein that was significantly regulated is predicted to be involved in cell wall/envelope biogenesis (Dde_0344, log2FC = 1.5), which is known to be associated with initial cell adhesion followed by biofilm formation (Ruhal and Kataria 2021; Bucher et al. 2015). Future investigation of these hypothetical proteins is required to reveal new molecular pathways involved in metal stress response and deepen our understanding of OA G20 copes with high Cu concentrations.

4.8. Perspectives on Copper Tolerance in OA G20 Biofilm

Our previous studies on the planktonic populations of OA G20 established that Cu concentrations greater than 15 μM have inhibitory effects on bacterial growth, triggering differential gene expressions to facilitate metal detoxification (Tripathi et al. 2022). Building upon these findings, we investigated biofilm formation under variable Cu concentrations (5, 15 and 30 μM). Interestingly, we observed enhanced biofilm development at 30 μM Cu compared to the control (0 μM). These results suggested the existence of an underlying molecular mechanism adapted by OA G20 to overcome Cu stress (Thakur et al. 2024). To elucidate these adaptive pathways, we further conducted a comparative proteomic analysis of 30 versus 0 μM biofilm samples, including intracellular and extracellular protein fractions. Our proteomic analysis revealed that biofilm formation under metal exposure involves a complex network of molecular mechanisms, rather than a single pathway, adapted by OA G20 to survive under Cu stress. Existing literature on bacterial metal‐biofilm interactions presents two complementary perspectives, some of which show that metal stress induces biofilm formation as a stress response (White and Gadd 2000; Völkel et al. 2018), whereas others demonstrate that biofilms protect bacterial populations against metal toxicity (van Wolferen et al. 2018; Harrison et al. 2006). This reflects a complex relationship between microbial communities and metal exposure. Based on the findings explained in the sections above and our previous studies, we hypothesize a multi‐stage adaptive response by OA G20 to overcome Cu stress.

Planktonic cells, when exposed to Cu ions, transition to the sessile lifestyle to protect themselves from toxic metal stress by regulating a cascade of interrelated molecular pathways. Biofilms exposed to Cu stress upregulate the redox‐maintenance enzymes, like FRs, Quinones and FMN reductase, which help bacteria neutralize oxidative damage and influence cell growth and adhesion (van Wolferen et al. 2018). The regulation of QS and chemotaxis proteins plays a crucial role in biofilm development by facilitating cell‐to‐cell communication and positioning cells optimally within the biofilm matrix, respectively (Prabhakaran et al. 2016). Additionally, QS within the biofilm is highly active, represented by the upregulation of the LuxR family member DctP, and coordinates the modulation of proteins that trigger biofilm matrix production. This biofilm matrix is maintained through the regulation of LPS transport proteins (Lpt), conferring structural integrity and creating a diffusion barrier, thereby limiting the penetration of Cu ions. In addition, the cells are embedded in EPS that can actively bind and sequester Cu ions at the periphery (Harrison et al. 2007). Biofilms exposed to Cu also exhibited variations in cellular phenotypes, like cell elongation, which were characterized by the regulation of proteins like MreB and FtsZ, which play a crucial role in cell division and elongation. This serves as a direct protection against Cu by decreasing the cell surface to volume ratio, thereby limiting the binding of toxic metal ions (Cesar and Huang 2017; Fernandes et al. 2018).

Simultaneously, the ABC transporter and efflux system efficiently export excess intracellular Cu, whereas periplasmic adaptor proteins bind Cu in the cell envelope, establishing a microenvironment for bacteria with decreased Cu toxicity. The bacteria signal transduction system comes into play and senses the safe microenvironments, thereby activating the flagella and motility proteins (e.g., upregulation of Fli‐, Flg‐ and Mot‐related proteins), aiding the cells to move towards the less toxic environment, and creating more robust biofilms compared to the control. This multi‐step regulation of various metabolic pathways within biofilms sets in motion a defence strategy that is coordinated by two‐component systems and NtrC family regulators, enabling bacteria to maintain essential functions despite Cu stress. This Cu‐specific enhancement of biofilm formation represents a direct adaptive strategy opted by OA G20 to not only survive Cu ion toxicity but utilize this stress signal to trigger a more developed biofilm architecture specifically engineered for metal resistance.

It is important to note that the hypothetical proteins explained above need further investigation as the samples investigated in the current study are taken from mature biofilms and lack a multi‐time point study. Future validation using protein analysis of samples taken from multiple time points, including biofilms and planktonic counterparts, is required to confirm these hypotheses. Although copper concentrations (5, 15, 30 μM) were systematically evaluated in our previous biofilm study (Thakur et al. 2024), with 30 μM selected as it demonstrates robust biofilm formation with significant planktonic growth inhibition, future studies across sub‐inhibitory concentrations would further distinguish adaptive from stress‐induced responses. The extracellular proteome was derived from culture supernatant; whereas cytoplasmic marker proteins did not show Cu‐dependent increases, baseline cytoplasmic protein presence cannot be entirely excluded. Although protease inhibitors were not used in this study, as they may introduce the possibility of partial protein degradation during sample handling (Shishkova and Coon 2021), no direct assessment of protein integrity (e.g., SDS‐PAGE analysis) was performed. However, the large number of proteins identified and the reproducibility of protein quantification across biological replicates in both fractions suggest that the overall proteome integrity was sufficient for robust comparative analysis. Orthogonal validation using Western blot or RT‐qPCR and functional gene knockout studies are required to further confirm these findings.

5. Conclusion

One of the key strategies that microorganisms employ to protect themselves from heavy metal stress is the formation of biofilms. The cells within a biofilm survive this toxicity by amalgamating a plethora of chemical and physiological responses. Our previous studies on OA G20 demonstrated the effect of Cu ions on cell growth, biofilm formation and cell morphology, along with transcriptomic responses of planktonic OA G20 to Cu ion stress. Here, the proteomics analysis of OA G20 biofilms formed under Cu stress revealed a subset of proteins that play an important role in cell survival and biofilm formation. For the GO MFs and BPs categories, the top enriched GO terms in the intracellular fraction were ATP binding (GO:0005524), oxidoreductase activity (GO:0016491), hydrolase activity (GO:0016787), cell wall organization (GO:0071555), isoleucine biosynthetic process (GO:00090971), and cell division (GO:0051301). Whereas in the extracellular fraction, metal ion binding (GO:0046872), magnesium ion binding (GO:0000287), GTP‐binding (GO:0005525), cell division (GO:0051301), dTDP‐rhamnose biosynthetic process (GO:0019305) and bacteriocin transport (GO:0043213) were enriched.

The current study also identified many proteins related to stress response: ABC transporters, efflux pumps, flagellar assembly, cell motility, cell morphology and chemotaxis. Additionally, this study observed many hypothetical proteins of unknown functions, with only 46 of the 133 hypothetical proteins identified using the MOTIF Search webserver. These hypothetical proteins were mainly predicted to be involved in secretion systems, flagellar motility, cell membrane biogenesis and lipid attachment. Although the role of these unidentified hypothetical proteins is unknown, they likely play a role in stress response and biofilm physiology.

Our current work demonstrates, for the first time, a detailed understanding of how these proteins interact and respond under Cu stress under sulphate‐reducing conditions. We have documented that our model SRB, OA G20, modulates its protein expression under stress, shedding light on the complex molecular mechanism adapted by OA G20 to survive and form biofilms. This study provides a foundation for identifying potential targets, like FtsZ, MreB and CheW, for regulating biofilm formation in SRB, providing insights into strategies for either biofilm mitigation or harnessing their bioremediation potential. Other omics techniques, like transcriptomics and metabolomics, along with gene knock‐out studies, are required to validate the role of potential protein targets involved in biofilm formation under Cu stress.

Author Contributions

Payal Thakur: conceptualization, methodology, software, formal analysis, investigation, data curation, writing – original draft, writing – review and editing, visualization, validation. Rajesh Kumar Sani: validation, formal analysis, writing – review and editing, supervision, funding acquisition, project administration. Abhilash Kumar Tripathi: software, data curation, validation, formal analysis, writing – review and editing, writing – original draft, visualization. Priya Saxena: validation, formal analysis, writing – review and editing. Boo Shan Tseng: formal analysis, writing – review and editing.

Funding

This work was supported by the National Science Foundation (1849206, 1920954).

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

File S1: Detailed protocol for LC/MS analysis.

File S2: Python codes for all the plots and figures.

File S3: Full set of differentially expressed proteins (30 μM vs. 0 μM) in both intra and extracellular groups.

File S4: Full set of significantly expressed proteins (|log2FC > 1|) in both intra and extracellular groups.

File S5: GO enrichment analysis for the intracellular DEPs.

File S6: GO enrichment analysis for the extracellular DEPs.

File S7: List of predicted function of hypothetical proteins identified through MOTIF Search Webserver.

File S8: List of proteins involved in stress response.

File S9: Proteins involved in efflux or transport.

File S10: List of proteins involved in flagellar assembly and motility.

File S11: List of proteins related to cell morphology.

File S12: Proteins related to two‐component system.

Figure S1: PCA of intracellular and extracellular protein fractions from OA G20 biofilms under 30 μM Cu and control (n = 3).

Figure S2: (a–c) MS/MS spectra for three replicates from extracellular fractions with no supplemented Cu (0 μM); (d–f) MS/MS spectra for three replicates from extracellular fractions with 30 μM Cu; (g–i) MS/MS spectra for three replicates from intracellular fractions with no supplemented Cu (0 μM); (j–l) MS/MS spectra for three replicates from intracellular fractions with no supplemented Cu (0 μM).

Data Availability Statement

The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via MassIVE repository with the dataset identifier PXD072968 and can be accessed at https://doi.org/10.25345/C5251FZ9H. All other data are presented within the Supporting Information or manuscript.