Effect of Quorum Sensing on the Ability of Desulfovibriovulgaris To Form Biofilms and To Biocorrode Carbon Steel inSaline Conditions

Giantommaso Scarascia,a Robert Lehmann,b Laura L. Machuca,c Christina Morris,d Ka Yu Cheng,d Anna Kaksonen,d

Pei-Ying Honga

aKing Abdullah University of Science and Technology, Water Desalination and Reuse Center, Biological and Environmental Science and Engineering Division, Thuwal,Saudi Arabia

bKing Abdullah University of Science and Technology, Environmental Epigenetic Program, Biological and Environmental Science and Engineering Division, Thuwal,Saudi Arabia

cCurtin University, Curtin Corrosion Centre, Department of Chemical Engineering, WA School of Mines: Minerals, Energy, and Chemical Engineering, Bentley, WesternAustralia, Australia

dCommonwealth Scientific and Industrial Research Organization, Land and Water, Floreat, Western Australia, Australia

ABSTRACT Sulfate-reducing bacteria (SRB) are key contributors to microbe-inducedcorrosion (MIC), which can lead to serious economic and environmental impact. Thepresence of a biofilm significantly increases the MIC rate. Inhibition of the quorum-sensing (QS) system is a promising alternative approach to prevent biofilm forma-tion in various industrial settings, especially considering the significant ecological im-pact of conventional chemical-based mitigation strategies. In this study, the effect ofthe QS stimulation and inhibition on Desulfovibrio vulgaris is described in terms ofanaerobic respiration, cell activity, biofilm formation, and biocorrosion of carbon steel.All these traits were repressed when bacteria were in contact with QS inhibitorsbut enhanced upon exposure to QS signal molecules compared to the control.The difference in the treatments was confirmed by transcriptomic analysis per-formed at different time points after treatment application. Genes related to lac-tate and pyruvate metabolism, sulfate reduction, electron transfer, and biofilmformation were downregulated upon QS inhibition. In contrast, QS stimulationled to an upregulation of the above-mentioned genes compared to the control.In summary, these results reveal the impact of QS on the activity of D. vulgaris,paving the way toward the prevention of corrosive SRB biofilm formation via QSinhibition.

IMPORTANCE Sulfate-reducing bacteria (SRB) are considered key contributors to biocor-rosion, particularly in saline environments. Biocorrosion imposes tremendous economiccosts, and common approaches to mitigate this problem involve the use of toxic andhazardous chemicals (e.g., chlorine), which raise health and environmental safety con-cerns. Quorum-sensing inhibitors (QSIs) can be used as an alternative approach to in-hibit biofilm formation and biocorrosion. However, this approach would only be effec-tive if SRB rely on QS for the pathways associated with biocorrosion. These pathwayswould include biofilm formation, electron transfer, and metabolism. This study demon-strates the role of QS in Desulfovibrio vulgaris on the above-mentioned pathwaysthrough both phenotypic measurements and transcriptomic approach. The results ofthis study suggest that QSIs can be used to mitigate SRB-induced corrosion prob-lems in ecologically sensitive areas.

KEYWORDS biocorrosion, biofilm, quorum sensing, sulfate-reducing bacteria,transcriptomic analysis

Citation Scarascia G, Lehmann R, Machuca LL,Morris C, Cheng KY, Kaksonen A, Hong P-Y.2020. Effect of quorum sensing on the ability ofDesulfovibrio vulgaris to form biofilms and tobiocorrode carbon steel in saline conditions.Appl Environ Microbiol 86:e01664-19. https://doi.org/10.1128/AEM.01664-19.

Editor Robert M. Kelly, North Carolina StateUniversity

Copyright © 2019 American Society forMicrobiology. All Rights Reserved.

Address correspondence to Pei-Ying Hong,peiying.hong@kaust.edu.sa.

Received 21 July 2019Accepted 13 October 2019

Accepted manuscript posted online 18October 2019Published

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Sulfate-reducing bacteria (SRB) are anaerobic microorganisms that utilize hydrogenand a range of organic compounds, such as lactate, acetate, pyruvate, and malate,

to reduce sulfate and produce hydrogen sulfide (H2S) (1). Sulfate reducers are generallythought to play an important role in the corrosion of metal surfaces exposed toseawater (2, 3). Although corrosion is mainly a chemical process involving metal oxidationand dissolution, it was found that SRB utilize hydrogen during sulfate reduction, which inturn affects the chemical dissolution of metal surfaces (4). Corrosive H2S produced bySRB further compromises the structural integrity of metals (i.e., chemical microbe-induced corrosion [CMIC]). Furthermore, members of SRB, such as Desulfovibrionaceaeand Desulfobulbaceae, can directly uptake electrons from the metal through pili,nanowires, or outer membrane proteins and cause corrosion (i.e., electrical microbe-induced corrosion [EMIC]) (4, 5).

For both CMIC and EMIC, the presence of a biofilm matrix establishes anoxic nichesin which SRB proliferate resulting in localized corrosion and pits (6). In addition, biofilmmatrix facilitates direct contact between the metal surface and bacterial outer mem-brane proteins (e.g., cytochromes and hydrogenases) or with electroconductive nano-wires (7, 8). In Desulfovibrio vulgaris, biofilm formation is dependent on filament andflagellar biosynthesis (9, 10). Coincidentally, in Pseudomonas aeruginosa and Vibriocholerae, some of their genes related to biofilm formation (e.g., rhamnolipids [11] andextracellular polymeric substance [12] production) are controlled by the quorum-sensing (QS) system. This led us to wonder whether biofilm formation and subse-quently biocorrosion could also be associated with QS in D. vulgaris.

QS is a communication system based on the exchange of small molecules calledautoinducers. When the density of cells reaches a threshold, autoinducer binds toreceptors to initiate a cascade of reactions that lead to either expression or repressionof certain genes (13). QS systems of Vibrio fischeri (14), Vibrio harveyi (15), and Pseu-domonas aeruginosa (16) are relatively well studied compared to QS systems in SRB,where the exact mechanism of the QS, as well as its linkage to biocorrosion, remainslargely unknown.

Data mining in the NCBI database revealed the presence of QS protein homologs inmany SRB (17). In particular, homologs of proteins involved in the QS-controlledphosphorylation cascade (LuxR and LuxO) and in the acyl homoserine lactone (AHL)synthesis were found in D. vulgaris (17, 18). This is verified by the detection of differentcarbon chains of AHLs, including C8-AHL, C10-AHL, and C12-AHL, in pure cultures of D.vulgaris (19, 20). Furthermore, it was found that exposing SRB to QS inhibitors in salineconditions diminished biofilm formation, sulfate reduction, and AHL production (20).This finding suggests a possible connection between QS and the above-mentionedbacterial functions. Nevertheless, a complete understanding of the QS effect at thegene level is still missing. The role of QS in SRB-induced biocorrosion is also not wellelucidated.

This study aims to understand the role of the QS system in SRB and to identify whichgenes correlate with the QS system using D. vulgaris as a model marine bacterium.Specifically, we sought to assess the influence of the QS system on biofilm formationand biocorrosion in a seawater environment. To achieve these objectives, the QSsystem of D. vulgaris was perturbed using either a stimulating cocktail of AHLs or aninhibitory cocktail of QS inhibitors (QSIs). The bacterial response to the two treatmentswas analyzed in terms of cell activity, lactate and sulfate consumption, biofilm forma-tion, and biocorrosion capacity. These bacterial traits were also investigated throughgene expression pattern upon treatment application. The results indicate a correlationbetween the expression or repression of genes (e.g., cell activity, biofilm formation,sulfate reduction, electron transfer, and lactate metabolism) with the stimulation orrepression of the QS system (through AHL or QSI application). This study provides animproved understanding on the role of QS in D. vulgaris in initiating biocorrosion, andit suggests the effectiveness of the QS inhibition approach to control SRB-associatedbiocorrosion.

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RESULTSEffect of QS modulation on planktonic bacteria. The ATP concentration per cell

increased at the same rate prior to AHL or QSI treatment (Fig. 1A). At 72 h, AHL or QSItreatment was applied. This treatment time was selected based on the previous findingthat, in D. vulgaris, a possible connection between sulfate reduction and the alterationof the QS system is most significant during the early exponential phase (20). After QSItreatment, ATP concentration per cell was significantly lower compared to the control(P � 0.05), with a difference that ranged from 0.12 to 0.30 pM/cell. In contrast, AHLtreatment resulted in an ATP concentration in average of 0.16 pM/cell higher than thatof control (Fig. 1A). Despite the difference in ATP concentration per cell, the differenttreatments did not result in a significant change (P � 0.05) in cell number amongcontrol, AHL, and QSI treatments (see Fig. S1 in the supplemental material).

Lactate was not utilized in the abiotic control but was consumed at similar rates inall the conditions prior to treatment (Fig. 1B and Table S1). After AHL application,lactate consumption rate was 0.45 � 0.05 mM/h and was significantly higher comparedto the other conditions (P � 0.05) (see Table S1 in the supplemental material). The totallactate utilization at the end of the experiment shows that QSI treatment resulted in thelowest total consumption compared to the control and AHL treatments (P � 0.05)(Table S1). Sulfate consumption (Fig. 1C) followed a similar trend of lactate utilization,with a significantly lower sulfate reduction rate upon QS inhibition (P � 0.05) (Table S1).

Due to increased lactate utilization rates upon AHL treatment, acetate was conse-quentially produced at a higher rate (0.71 � 0.10 mM/h) compared to both control andQS inhibition condition (P � 0.05) (Table S1), and the acetate concentration stabilizedat ca. 48 mM (Fig. 1D).

Biofilm and surface characterization. Coupon biofilm analysis showed that asignificantly higher number of cells and ATP per surface unit were obtained with AHLtreatment, whereas QSI addition significantly decreased both parameters compared tothe control (P � 0.05) (Fig. 2A).

FIG 1 Concentrations of ATP per cell (A) and of lactate (B), sulfate (C), and acetate (D) in the planktonic phase during the experimentaltime in control, QSI [100 �M (Z-)-4-bromo-5-(bromomethylene)-3-butyl-2(5H)-furanone, 100 �M 3-oxo-C12-(2-aminocyclohexanone),and 5 mM �-aminobutyric acid], and AHL (N-octanoyl-homoserine lactone [C8-HSL], N-decanoyl-homoserine lactone [C10-HSL], andN-dodecanoyl-homoserine lactone [C12-HSL], 5 �M each) treatments and under abiotic control conditions. The dashed red lineindicates the moment of the treatment injection (72 h). Error bars show the standard deviations from three biological replicates.Statistical differences were evaluated by one-way ANOVA, with a confidence level of 95% (P � 0.05).

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QSI and AHL treatments altered the impact of biocorrosion on the carbon steelcoupon surface. Surface roughness and maximum pit depth (Fig. 2B) were both higherwhen the coupons were in AHL-treated cultures compared to the control (P � 0.05),whereas these surface topography values were significantly lower when QSI wasapplied (P � 0.05). The extent of surface biocorrosion can be observed in Fig. S2Athrough S2C, where scanning electron microscopy (SEM) images showed higher densityof pits was obtained when bacteria were in contact with the AHL cocktail. The mediumalone caused slight or no signs of biocorrosion (Fig. S2D). Atomic force microscopy(AFM) photos of coupon surfaces reiterated the same observation (Fig. S3). No apparentsurface pits were observed in abiotic controls that contained only the AHL and QSImolecules (Fig. S4).

Corrosion evaluation through electrochemical and weight loss analysis. Linearpolarization resistance and weight loss analyses were conducted to quantitativelyevaluate the respective daily and total corrosion rates arising from the differenttreatments. An increase in the corrosion rate was observed at day 4, after 1 day fromtreatment exposure, for all of the biotic conditions. AHL-treated samples showed arapid increase in the corrosion rate that reached 1.1 mm/year, while QSI treatmentresulted in a lower increase in the corrosion rates compared to control and AHLtreatment (Fig. 2C). Under all conditions, corrosion rates started to decrease after day5. Weight loss analysis further confirmed that the highest total corrosion rate wasachieved upon AHL treatment (0.41 mm/year, P � 0.05), while the lowest was obtainedin the presence of QSI (ca. 0.08 mm/year, P � 0.05) (Fig. 2D).

Overview of gene expression. Genes that correlate with the QS system perturba-tion were selected based on the scoring system presented in the supplementalmaterial. A total of 162 genes, accounting for 4.6% of the total genes present in D.vulgaris, were found to correlate with QS stimulation or inhibition using a score of �2.Particularly, 45 of these genes (1.3% of the total genes) were highly correlated with theQS system (a score of �3). Figure 3 shows the summarized numbers of differentiallyexpressed genes, while Table S2 lists the gene fold changes compared to the control

FIG 2 Coupon biofilm ATP concentration and cell density (A), surface roughness index and maximum pit depth (B), corrosionrate calculated through linear polarization resistance (C), and total corrosion rate measured by weight loss analysis (D) in thecontrol, QSI, and AHL treatments (as described in the legend to Fig. 1) and under abiotic control conditions. Error bars showthe standard deviations from three biological replicates. Statistical differences were evaluated through one-way ANOVA, witha confidence level of 95% (P � 0.05).

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for each of the treatments at each time point. In general, at 6 h of AHL or QSI treatment,the number of downregulated genes was comparable between the two treatments,although there were more genes showing upregulation in the presence of AHL, inparticular the ones related to biofilm formation, electron transfer, and the regulatorygenes (Fig. 3). Subsequently, stimulation of the QS system through AHL treatmentresulted in an upregulation of most of the genes at 24 and 48 h. An opposite trend wasobserved upon QSI treatment, where most of the genes were downregulated (Fig. 3).

Regulatory genes. Both QS stimulation (by AHL treatment) and inhibition (by QSItreatment) led to expression of genes encoding regulatory proteins such as transcrip-tional and response regulators and histidine kinases (Table S2.1). Transcriptional reg-ulator and histidine kinase are part of the gene machinery that allows the QS systemto regulate different bacterial functions. A histidine kinase and two transcriptionalregulators belonging to the LuxR family were strongly correlated with QS stimulationor inhibition, indicating that the assigned scoring system is able to pinpoint QS-associated genes. Furthermore, some of these genes that correlated with the QSstimulation or inhibition were found to be grouped in the same operons and thereforelikely to work in the same pathway or to interact with each other (Table S2.1).

Cell activity and membrane transport. The two treatments showed an importantinfluence on cell activity. ATP synthase genes were upregulated 24 and 48 h from AHLaddition and downregulated after QSI treatment compared to the relative control (Fig.3 and 4, in yellow), suggesting a higher cellular activity in AHL-treated samplescompared to the other conditions. This observation is in agreement with the higher ATPconcentration measured in AHL-treated samples (Fig. 2A).

Genes encoding the large and small subunits of ribosomal proteins were upregu-lated by AHL treatment, indicating higher protein production and cell activity (Fig. 3).Conversely, QSI treatment had a slightly lower impact in the downregulation of thesegenes compared to the control. From this group, four large and four small ribosomalsubunits were strongly correlated with the QS system modulation (Table S2.3) and werelocated in a total of three operons (Table S2.3).

Similarly, the expression of genes related to membrane transfer, particularly thoseencoding ATP-binding cassette (ABC) transporters, also correlated with the AHL and QSItreatments (Table S2.4). Some of the ABC transporter genes were involved in thebiogenesis of cytochromes and thus facilitate electron transfer.

FIG 3 Numbers of differently expressed genes grouped in functions in AHL and QSI treatments at three time points compared to therelative control. Upregulated genes are shown in red; downregulated genes are shown in blue. The size of the circle represents thenumber of differently expressed genes (DEGs).

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Metabolism and anaerobic respiration. D. vulgaris is able to use various electrondonors, such as lactate, pyruvate, and hydrogen, to reduce sulfate and generate energy(21). Figure 4 illustrates genes related to lactate and pyruvate metabolism, sulfatereduction, and electron transfer that were affected by QS system perturbation in ourstudy.

Genes related to lactate oxidation, such as lactate dehydrogenase (ldh), pyruvate-flavodoxin oxidoreductase (por) and acetate kinase (ack), were upregulated in AHL-treated samples at 24 and 48 h from exposure compared to the control (Fig. 4, ingreen). In QSI-treated samples, these genes were instead downregulated at 24 h fromexposure, while at 48 h, QSI treatment affected only a smaller number of genes (TableS2.5). Also, pfl encoding pyruvate formate-lyase correlates with QS treatment.

Genes involved in the sulfate reduction pathway (Fig. 4, in blue), including sulfateadenylyltransferase (sat), adenylsulfate reductase (apsAB), and dissimilatory sulfite re-ductase (dsrABC), were affected by the inhibition or the stimulation of the QS system.Among them, three genes related to the dissimilatory sulfite reductase were groupedin the same operon and most likely transcribed in the same pathway. Furthermore, asimilar trend was observed for genes encoding sulfur carrier and sulfotransferase (TableS2.6). This is with the exception of the ppa gene, which encodes proteins involved inthe hydrolysis of pyrophosphate.

Electron transfer. Electron carriers are required for sulfate reduction and to estab-lish proton motive force. Figure 4 (in red) and Table S2.7 showed that genes encodingferroxidin (Fd), cytochromes (Cyt), hydrogenases (Hase), and formate dehydrogenase

FIG 4 Simplified representation of the D. vulgaris cell, including proteins encoded in genes related to lactate and pyruvate metabolism(in green), sulfate reduction (in blue), electron transfer (in red), and ATP synthases (in yellow). Proteins shown in a solid color are encodedin genes that are controlled by the QS system (protein complexes are shown in a solid color when one of their components was controlledby QS). A dark or light color represents a higher or a lower grade of QS influence, respectively. A net pattern indicates proteins encodedby genes that were not impacted by the QS modulation (CM, cytoplasmic membrane, OM, outer membrane). The figure was adapted fromStrittmatter et al. (44).

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(Fdh) were strongly correlated with the addition of either AHL or QSI molecules. Someof the cytochromes were transcribed and regulated together in the same operons.Genes associated with membrane complexes such as DsrMKJOP, QmoABC, Coo, andRnf were also affected by the two different treatments (Table S2.7). In particular, genesrelated to QmoABC were found in the same operon, together with the ones related toApsAB (Table S2.6 and S2.7), even if they participate in two different bacterial functions,namely, electron transfer and sulfate reduction. However, not all electron transfer genesare affected by QS. For example, Tmc, Hmc, Qrc, Nuo, and Och, most of which areassociated with membrane complexes, were not influenced by any of the treatmentscompared to the control (Fig. 4, net pattern).

Biofilm formation. Genes associated with biofilm formation were related to flagel-lar biosynthesis, pilus assembly, and extracellular polymeric substance (EPS) synthesisand transport. Seven genes associated with pilus assembly (rcpC, tadB, and tadD) andEPS (DVU_0670 and glycotransferases) were highly correlated with the addition of bothtreatments (Table S2.8). Some of these genes were transcribed together in the sameoperon (Table S2.8).

CRISPR genes. Almost all the genes encoding clustered regularly interspaced shortpalindrome (CRISPR)-associated proteins were upregulated compared to the controlafter AHL treatment (Fig. 3). However, unlike the other genes in which QSI treatmentwould lead to a corresponding downregulation of the same genes, QSI inhibition didnot have any impact on these CRISPR genes.

Hypothetical proteins. Seven hypothetical proteins with unknown functions werealso affected by both AHL and QSI treatments (Table S2.10). Among them, two geneswere strongly correlated with the QS alteration. One of these genes is located in acluster of other genes with unknown functions, while the second one is surrounded bygenes encoding bacteriophage-related proteins (Fig. S5).

Baseline gene expression change in time in control samples. Given that D.

vulgaris naturally produces AHL, a separate analysis was made for the gene expressionsin the control without any additional AHL or QSI application. This is done to determinewhether differential gene expressions described in earlier subsections when comparingAHL application versus control at each individual time point were also observed whenAHL is produced at baseline levels. Over time, some of the genes in Table S2 weredifferentially expressed in the control samples. In general, a downregulation trend wasobserved when comparing the gene expression of the control samples at 24 and 48 hwith the one at 6 h (Table S3). All of these genes were even more downregulatedcompared to the same control samples after QSI addition. However, genes involved inbiofilm formation and in the regulatory functions were mostly upregulated at time 24and 48 h, coinciding with an increase in cell density and likely AHL amount produced(Table S3). In addition, by 48 h, some genes related to membrane transport andelectron transfer were also upregulated, although the majority of the genes in thesecategories remained downregulated compared to 6 h. However, genes that wereupregulated in control samples were expressed at an even higher level when AHL wasfurther applied. For example, the two LuxR family genes that were found to beupregulated in the 48-h control samples were even more upregulated when wecompared AHL samples to the relative control at the same time point (Table S2.1). Thisconfirms the ability of our AHL treament to increase the detection sensitivity of geneexpressions, while not deviating too much from the actual response of the bacterialculture.

Confirmation analysis of LuxR family motif sequences. The expression of genesis regulated by the presence of transcription factors that control the transcription of thegene. To confirm that the different genetic expression was effectively influenced by QSsystem alteration, we searched for LuxR family boxes by sequencing from 400 bpupstream to 50 bp downstream of each gene in Table S2. A total of 238 hits with a Pvalue of �0.05 were found (Table S4). The number of hits was greater than the 162genes detailed in Table S2 because some of these genes were characterized by more

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than one motif sequence. Particularly, for 116 genes over 162 genes influenced by theQS system, we found at least one transcription factor sequence related to the LuxR orthe las-rhl family. This indicates that most of the genes that were affected by theaddition of the treatments were characterized by transcription factor related to QS. Inaddition, by performing the Benjamini-Hochberg procedure to correct the initial motifprediction significance P values for the multiple hypothesis tests, a more stringent qvalue was obtained. Based on this, we found that 19% of the hits had a q value of �0.05(Table S4 in boldface) and were related to genes of various bacterial functions con-nected to the LuxR family transcription regulator vqsR.

DISCUSSION

Understanding the QS functionality in SRB represents a crucial step to develop a QSinhibition approach and to effectively reduce biofilm formation and biocorrosion.Earlier studies revealed the presence of proteins that are homologous to the transcrip-tional regulator LuxR in D. vulgaris Hildenborough (17, 18). In the present study, twogenes encoding proteins of the LuxR family were upregulated naturally in the controltemporal baseline (Table S2.1). D. vulgaris, in fact, produces AHL molecules itself, withincreasing cell density (20). Moreover, these two genes were strongly correlated withthe QS system alteration (Table S2.1), showing an even higher magnitude of up- ordownregulation in AHL and QSI samples, respectively. In addition, upregulation ordownregulation of other transcriptional regulator and histidine kinase genes followedQS stimulation and inhibition, respectively (Fig. 3). Proteins encoded by these genes arefundamental because they are part of the cellular machinery that allows the QS systemto regulate different bacterial functions (13). Interestingly, two of these genes encodeQS family proteins (YebC and LysR) that were found to control biofilm formation andAHL production in P. aeruginosa (22, 23). These transcriptional regulators can possiblybe part of the QS system in D. vulgaris and regulate functions similar to those in P.aeruginosa. More detailed studies are required to determine the individual role of theproteins encoded by these genes in D. vulgaris.

These observations suggest the ability of the applied treatments and analysisconducted in this study to elucidate pathways, including those already known, that areinvolved in QS signal response. For instance, it was observed that energy productionand protein transcription in D. vulgaris correlated with AHL and QSI treatments. ApplyingAHL or QS inhibitors did not impact the total cell number (Fig. S1), confirming that QSdoes not affect bacterial growth, but it affected cell activity, the capacity to generateenergy and to produce proteins and enzymes. In fact, the amount of ATP per cellproduced after AHL treatment was higher compared to the other conditions (Fig. 1A).This greater cell activity was confirmed by the transcriptomic analysis. Upregulation anddownregulation of genes related to ATP synthase (Fig. 4, in yellow) and protein transcrip-tion (ribosomal subunit genes) correlated with AHL and QSI treatment, respectively (Fig. 3).

Besides affecting cellular activity and the production of proteins and enzymes, QSalteration appeared to also correlate with the expression of genes related to transportof materials through the membrane. For example, ABC transporters are generallyinvolved in the transport of nutrients and amino acids into the cell. Many genesencoding these proteins showed upregulation or downregulation compared to thecontrol depending on the type of QS perturbation (Fig. 3). In addition, the same wasobserved for the expression of genes encoding membrane efflux pumps (Table S2.4),which facilitate the transfer of protons across the periplasmic membrane and arerequired to sustain a higher ATP synthesis. Furthermore, some of the genes in this classencoded transporter protein involved in the biosynthesis of cytochromes. Upregulationof membrane transport-related genes was also observed when a QS signal generation-deficient mutant of P. aeruginosa was provided with AHL to stimulate the QS system(24).

The higher activities associated with transporters and efflux pumps could haveindirectly resulted in the higher cell activity and protein synthesis discussed earlier forD. vulgaris. However, the expression of genes related to other membrane proteins

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involved in the electron transfer to the sulfate reduction pathway (Tmc, Hmc, and Qrc)was not affected by QS (Fig. 4, in net pattern). Unlike DsrMKJOP and QmoABC, whichare considered essential for sulfate reduction and showed differential gene expressionsupon AHL and QSI applications, Tmc, Hmc, and Qrc are not always present in all SRB,and they play a role only in the presence of certain organic substrates (25). In contrast,along with heterodisulfide (hdr) reductase, dsrMKJOP, and qmoABC, other genes en-coding periplasmic hydrogenases, cytochromes, and ferredoxins also correlated withQS. These results are in agreement with an earlier study on P. aeruginosa, in which thestimulation of the QS system led to the upregulation of genes related mainly tocytochromes (11).

As expected, considering the regulation of electron transfer genes by QS modula-tion, sulfate reduction was also observed to likewise be affected by both AHL and QSItreatments (Fig. 1B and C). For instance, several genes involved in sulfate reduction andlactate metabolism were differentially expressed in the presence of AHL and QSItreatments compared to the relative control (Fig. 3). D. vulgaris oxidizes lactate topyruvate and then, with the addition of acetyl coenzyme A, to acetate. Pyruvate canalso be converted to formate through the pyruvate-formate lyase (pfl). Formate is thenoxidized to CO2 by formate dehydrogenase (fdh), an enzyme involved in the periplas-mic electron movement. Electrons from lactate are available for sulfate reduction. Whensulfate is internalized, it is converted to adenylylsulfate (APS) by the sulfate adenylyl-transferase (sat). APS is reduced to sulfite by the APS reductase (aprAB) and thenconverted to hydrogen sulfide by the dissimilatory sulfite reductase (dsrABC) (26).Particularly, apsB and qmoABC were found in the same operon, indicating that theywere transcribed and regulated together, even if they are associated with differentbacterial functions. This suggests the interconnection of electron transfer and sulfatereduction pathways and the synergistic QS effect on both of them. All of the citedessential genes involved in lactate oxidation and sulfate reduction pathways showed acorrelation with QS modulation in our study (Fig. 4, in green and in blue, respectively,and Table S2.5 and S2.6). A similar impact on metabolism-related genes was alsodescribed for Burkholderia glumae, in which phosphate metabolism and the biosyn-thesis of various amino acids were controlled by QS (27). Furthermore, it was found thatAHL addition led to the upregulation of a gene encoding a sulfite reductase in P.aeruginosa (11). P. aeruginosa is a thiosulfate reducer possessing part of the geneticmachinery that is found in D. vulgaris. A previous study also showed that D. vulgarisexposed to each individual compound of the QSI cocktail used in our study showed adecline in sulfate reduction (20), suggesting a relationship between sulfate reductionand QS. This finding, together with our results, supports the idea that sulfate reductionand subsequently biocorrosion might be indeed linked to QS. Although QSI treatmentwas correlated with a general downregulation of the above-cited bacterial functionsafter 6 h of treatment, the AHL treatment effect was not as apparent after 6 h oftreatment (Fig. 3). This could be due to a longer bacterial acclimatization to the AHLtreatment or to a slower molecular assimilation of AHL compared to QSI.

In this study, the amount of biofilm on the carbon steel surface formed under thedifferent conditions (Fig. 2A) correlated with the expression of genes related to EPSproduction and flagellum and pilus biosynthesis (Tables S2.7 and S2.8). The expressionof these genes was affected in an opposite way depending on whether AHL or QSI wasapplied (Fig. 3). The same genes were also upregulated over the temporal baseline ofthe control samples, suggesting that an actual gene response was captured in ouranalysis despite artificially inflating the amount of AHL concentrations for increasingdetection sensitivity. These genes were previously found to be crucial for biofilmformation in D. vulgaris (9, 10). By impacting biofilm formation, QS could indirectlyaffect biocorrosion (Fig. 2B to D). Surface contact facilitated by the biofilm structurecould enhance the EMIC process both directly, through nanowires (28) and cyto-chromes (8), or indirectly via electron carriers (29). Furthermore, the higher sulfateconsumption and the upregulation of genes related to sulfate reduction in AHL-treated

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samples might indicate higher production of H2S in the environment. This gas is highlycorrosive, and it reacts with the metal surface, stimulating the corrosion process.

This study also unveiled a less described role of QS in bacterial protection. TheCRISPR adaptive immune system provides resistance to bacteriophages (30). Recentstudies have shown that QS can modulate the activity of the CRISPR system byactivating the expression of cas genes (27). It was proposed that maintaining theCRISPR system under QS control allows an efficient response when the risk of phageinfection is high (31). Likewise, we found that AHL addition was correlated with anupregulation of different CRISPR genes (Fig. 3 and Table S2.9). In addition, from theanalysis of the position in the D. vulgaris genome of QS-controlled genes with unknownfunction, it was observed that the hypothetical protein 205 (Hp205) is placed next togenes related to phage eliminase and phage tail (Fig. S5). However, CRISPR genes werenot downregulated when QSI inhibitors were applied, suggesting a different, non-QS-based pathway of silencing these genes. Further studies are required to clarify theeffect of QS on these functions in D. vulgaris.

In summary, QS alteration is correlated with the modulation of different key func-tions, including ATP production, protein transcription, membrane transport, lactateoxidation, sulfate reduction, biofilm formation, and biocorrosion in D. vulgaris. QS-associated effects were observed at both phenotypic and molecular levels. At themolecular level, a lot of the genes that are differentially expressed were characterizedby the transcription regulator vqsR. However, further and more in-depth studies arerequired to determine the exact mechanism or causative effect of AHL and QSI on theQS system of D. vulgaris. Nevertheless, our findings provide important indications aboutthe role of QS in SRB, and open up the possibility to exploit a QS inhibition approachto reduce biofilm formation and biocorrosion related to SRB.

MATERIALS AND METHODSBacterial cultivation conditions. Desulfovibrio vulgaris Hildenborough (21) was propagated in

marine Desulfovibrio Postgate medium (DSMZ) with concentrations of 50 mM lactate and 25 mM sulfate.The medium had the following composition: 25.0 g/liter NaCl, 0.5 g/liter K2HPO4, 1.0 g/liter NH4Cl,2.4 g/liter Na2SO4, 0.1 g/liter CaCl2·2H2O, 0.97 g/liter MgSO4, 0.005 g/liter FeSO4·7H2O, 1.0 g/liter yeastextract, and 0.1% (wt/vol) sodium resazurin as an O2 indicator. After heat sterilization, the medium wassupplemented with filter-sterilized (0.22-�m pore size) sodium lactate (50 mM) and a solution composedof 0.1 g/liter sodium thioglycolate and 0.1 g/liter ascorbic acid. The pH of the medium was adjusted to7.5 and aseptically transferred to sterile tubes or vials sealed with butyl rubber stoppers. The medium waspurged with N2 for 15 min and placed in the anaerobic chamber (Coy Laboratory Products, Inc., GrassLake, MI), where L-cysteine (100 mg/liter) was added as an oxygen scavenger. For all of the experiments,a 5% (vol/vol) bacterial inoculum was maintained, and the cultures were incubated at 30°C withoutshaking.

Anaerobic reactor setup. Four serum bottles were equipped with five carbon steel coupons (1030;ChemWorld, Taylor, MI), each with a surface area of 1.4 cm2. Coupons were wet polished with sandpaperup to 600-grit finish, cleaned with ethanol, and dried with nitrogen. After UV sterilization, the couponswere immersed in 800 ml of the marine DSMZ. The medium in each serum bottle was purged with N2

for 1 h before bacterial inoculation in the anaerobic chamber. One serum bottle was not inoculated andserved as an abiotic control. All the serum bottles were incubated at 30°C without shaking for 7 days.After 72 h of incubation, one serum bottle was injected with a cocktail of N-octanoyl-homoserine lactone(C8-HSL), N-decanoyl-homoserine lactone (C10-HSL), and N-dodecanoyl-homoserine lactone (C12-HSL)(Cayman Chemical, Ann Arbor, MI), each at a concentration of 5 �M (AHL treatment). The concentrationsof the three AHLs used in our study were not physiologically relevant since they are higher than thebaseline concentration produced by D. vulgaris. However, it was necessary to excite the bacterial QSsystem and to improve detection sensitivity when performing subsequent transcriptome sequencing(RNA-seq) analysis, as shown in an earlier study (11). At the same time, one serum bottle was injectedwith a cocktail of QSIs used in a previous study (20). The cocktail was composed of (Z-)-4-bromo-5-(bromomethylene)-3-butyl-2(5H)-furanone at 100 �M, 3-oxo-C12-(2-aminocyclohexanone) at 100 �M,and �-aminobutyric acid at 5 mM (QSI treatment). The treatments were spiked after 72 h from incubationbased on the indication of our earlier study, which showed that the alteration of the QS system has amore pronounced effect in the early exponential phase (20). The remaining inoculated serum bottle wasnot injected, serving as biotic control. The experiment was repeated to obtain a total of three biologicalreplicates. In addition, the possible impact of the two treatments on the coupon surface was assessed.An abiotic experiment with the addition of QSI and AHL cocktail was performed in triplicates.

Planktonic cell analysis. Bacterial culture aliquot (5 ml) was sampled every 12 h from the serumbottles in an aseptic manner. The sampling was conducted in the anaerobic chamber to avoid anyoxygen contamination.

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To assess cell activity during the incubation period, the level of ATP per cell was calculated. For cellenumeration, 100-�l portions of bacterial suspension were diluted 103 times, stained with SYBR green(Thermo Fisher Scientific, Waltham, MA), and counted by BD Accuri C6 flow cytometer (BD Bioscience,Franklin Lakes, NJ). The ATP concentration was quantified using a Celsis amplified ATP reagent kit andan Advance luminometer (Celsis, Westminster, United Kingdom). Theoretically, 2 mol of lactate con-sumed and 1 mol of sulfate reduced led to the production of 2 mol of acetate (32), as shown in thefollowing reaction:

2C3H5O3– � SO4

2– � 2C2H3O2– � 2HCO3

– � HS– � H�

Lactate and acetate concentrations were quantified by using a high-performance liquid chromato-graph equipped with an HPX-87 H ion exchange column (300 by 7.8 mm; Bio-Rad, CA) and a UV detector.Sulfuric acid (5 mM) was used as a mobile phase at a flow rate of 0.6 ml/min. The sulfate concentrationin the planktonic phase was quantified using an ICS-1600 ion chromatograph (Dionex Corporation,Sunnyvale, CA) with KOH as an eluent. Data from the chromatography analysis were processed usingChromeleon 7.0 software. The lactate, acetate, and sulfate consumption rates were calculated before andafter the treatments.

Coupon biofilm harvesting and surface analysis. After 7 days of incubation, the coupons from theserum bottles were harvested aseptically, and then biofilm and surface characterization was performedto assess the effect of the different treatments. All of the coupons from each serum bottle were washed,placed separately in 1 ml of 1� phosphate-buffered saline (PBS), and sonicated for 5 min to detach thebiofilm from the metal surface. The cell suspension was assessed for the number of attached cells andthe ATP concentration using the protocols described above. The other three coupons were removedfrom the PBS and placed in Clark solution for 30 s to remove any recalcitrant biofilm and corrosionproducts (33).

One coupon was observed under an FEI Teneo SEM (Thermo Fisher Scientific, Hillsboro, OR) toexamine the degree of surface corrosion and the presence of pits caused by the formed biofilm. Thesecond coupon was analyzed through AFM to determine the surface roughness. For each coupon, twoareas of 50 by 50 �m each were analyzed using Bruker Dimension ICON equipment (Santa Barbara, CA)in soft tap mode at a constant spring of 40 N/m and a resonant frequency of 300 kHz. The AFM imageswere analyzed on Pico image software (Keysight Technologies, Inc., Santa Rosa, CA). The last coupon wasused to determine the maximum depth of the pits using a Dektak profilometer (Bruker, Billerica, MA). Foreach coupon, two sections 500 �m in length were analyzed. In addition, SEM, AFM, and surface profileanalyses were performed to assess the abiotic effects of both AHL and QSI molecules alone on thecoupon surface.

Electrochemical and corrosion analysis. Quantitative evaluation of biocorrosion was obtainedthrough electrochemical measurements and weight loss analysis. Four Communicable Disease Centrebioreactors (BioSurface Technologies, Bozeman, MT) equipped with five carbon steel coupons (1030;BioSurface Technologies, Bozeman, MT) were operated at 30°C with continuous stirring in batch modefor 7 days with continuous N2 purging. The reactors were filled with 600 ml of marine DSMZ, and threeof them were inoculated (5%) with D. vulgaris in the exponential phase. One reactor was not inoculated(i.e., abiotic control). After 72 h, one reactor was injected with the QSI cocktail and one with the AHLcocktail. The abiotic control was inoculated with both cocktails, while the remaining inoculated reactorwas used as control. Coupons in the reactors (surface area, 1.3 cm2) were previously electrocoated witha protective layer of Powercron 6000CX (PPG Industrial Coatings), and one surface (exposed surface) waspolished up to 600 grit finish. Three coupons for each reactor were weighed before to initiate theexperiment for the weight loss analysis.

Two coupons were soldered with a copper wire, and they served as working electrode for theelectrochemical measurements. A platinum-coated mesh was used as counterelectrode, and a double-junction Ag/AgCl electrode (3.5 M) was used as reference electrode. The reference electrode was held ina Luggin capillary filled with agar (1.5% [wt/vol]) containing 3% KCl (wt/vol). All electrochemicalmeasurements were conducted using a Gamry-600 potentiostat connected to an electrochemicalmultiplexer ECM8 (Gamry Instruments, Warminster, PA). The linear polarization resistance from �0.1 to0.1 V, with a scan rate of 1 mV/s, was measured daily to obtain the corrosion rate using the Gamrysoftware. At the end of the incubation exposure, three coupons were weighed to measure the weightloss after biofilm and corrosion product removal using Clark solution. The total corrosion rate related toall the incubation times expressed as millimeters per year was calculated according to standard methods(33). The experiment was repeated twice more for a total of three replicates.

RNA extraction and sequencing. Samples from the inoculated serum bottles (control, AHL, and QSItreatments) were taken after 6, 24, and 48 h from the treatment application. Biomass preservation andRNA extraction were performed as described previously (34). Briefly, 15 ml of suspended culture wascentrifuged at 6,500 � g for 30 min, and the pellet was resuspended in 2 ml of 1� PBS. Thereafter, 4 mlof RNAprotect cell reagent (Qiagen, Hilden, Germany) was added to avoid RNA degradation, and thesolution was incubated at room temperature for 5 min. After incubation, the mixture was centrifuged at6,500 � g, and the pellet was stored at – 80°C until RNA extraction. RNA was extracted using an RNeasyMidikit (Qiagen), including a DNase treatment, and the RNA concentration was measured using anInvitrogen RNA HS Qubit 2.0 assay kit (Thermo Fisher Scientific).

The RNA quality was assessed with a 2200 Tapestation bioanalyzer (Agilent Technologies, Santa Clara,CA). Afterward, the samples were enriched in mRNA by rRNA removal using a Ribo Zero rRNA removalkit (Illumina, San Diego, CA). Finally, RNA-seq libraries were prepared and submitted to the KAUSTgenomic Core Lab for RNA-seq on an Illumina HiSeq 4000 platform.

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RNA transcriptomic analysis. D. vulgaris DNA was extracted and the whole genome was sequencedusing the PacBio platform. The genome sequence was assembled as described elsewhere (35–37). Thestructural annotation of the final genome assembly was performed with Rast (38). Genome assemblyrevealed the presence of a circular chromosome of 3,526,512 bp and a plasmid of 201,796 bp, accountingfor a total of 3,538 genes. The in-house assembled genome shared the most similarity with the referencegenome of Desulfovibrio vulgaris Hildenborough (21), indicating no contamination of the SRB culture.

Transcriptomic analysis was performed with CLC Genomic Workbench 8.0 (CLC Bio, Cambridge, MA),as described elsewhere (39). The in-house assembled and annotated D. vulgaris genome described abovewas used as reference genome. RNA-seq reads were first mapped to the whole bacterial genome toassess the quality of the samples and the absence of contamination. The rest of the analysis wasperformed mapping the reads only to the coding sequence of the annotated genome. Reads weremapped to the genome only if the fraction aligned sequence was �0.9 and if the number of nucleotidesmatching other genome regions was �10. The percentage of mapped reads to both coding sequencesonly and to the whole genome can be found in Table S5.

After read mapping, biological replicates were assigned to the same category, and a mean expressionvalue was calculated. In addition, a scaling correction was applied to normalize each expression valuewith the total number of reads. Normalized gene expression value was defined as reads per kilobase permillion (RPKM). The different effects of each of the two treatments were compared to the control at thesame time point. A Baggerly proportion-based test was used for statistical comparison (40). A fold changeof 2 and a P value of �0.05 were selected as threshold parameters in the selection of differentlyexpressed genes. Based on their upregulation (fold change, �2) or downregulation (fold change, ��2)in the two treatments, a scoring system was applied to each gene. A minimum total score of 2 was usedto consider a gene to be likely correlated with the QS system. A gene with a score of �3 was consideredstrongly correlated with the QS system. Genes that did not fit these parameters (fold change, P value, andscoring system) were not considered for further analysis. Genes that showed a strong correlation with theQS were analyzed to evaluate whether other genes in their same operon were also affected by QSmodulation. The operon structure was found in the OperonDB database. Operon grouping for thisdatabase was performed through an algorithm that infers the probability that two adjacent genesbelong or not to the same operon (41). In addition, to further evaluate the baseline temporal trend forthe control samples, the gene expression of control samples after 24 and 48 h from the moment of thetreatments in AHL and QSI samples was compared to the one after 6 h. More details are provided in thesupplemental material.

Transcription factor binding site analysis. The analysis of LuxR family box sequencing wasperformed to confirm that the different genetic expression was effectively influenced by QS systemalteration. Fimo v5.0.5 (42) was used to predict transcription factor binding site motifs in a sequencewindow reaching from 400 bp upstream to 50 bp downstream of each gene transcriptional start site. Theresults were filtered, retaining only hits with a P value of �0.05. In addition, to correct the initial motifprediction significance P value for the multiple hypothesis test, we performed the Benjamini-Hochbergprocedure. This test provides the minimal false discovery rate (FDR), a more stringent threshold at whichthe corresponding P value is considered significant. Hits with an FDR q value of �0.05 were furtherinvestigated. Fimo was provided with binding site motifs of 13 transcription factors of the LuxR family,obtained from the collectTF database (43). The following transcription factors were included (transcrip-tion factor symbol followed by the UniProt identifier in parentheses): hapR (A0A0H3Q915), lasR (P25084),lasR (P54292), luxR (A7MXJ7), luxR (B5EV73), luxR (P35327), opaR (Q79YV4), rsaL (G3XD78), smcR(Q7ME71), traR (P33905), vpsT (Q9KKZ8), vqsR (Q9I0P6), and vsrD (Q8XVU0). In addition, the las-rhl motifdefined by Schuster et al. (11) was also included.

Statistical test. To evaluate statistical differences, one-way analysis of variance (ANOVA) wasperformed, with a confidence level set at 95% (P � 0.05).

Data availability. The raw read data are available on the European Nucleotide Accession Short ReadsArchive repository under accession number PRJEB33204. The assembled genome is available from theENA SRA repository under accession number ERS3567812.

SUPPLEMENTAL MATERIALSupplemental material for this article is available online only.SUPPLEMENTAL FILE 1, PDF file, 1.6 MB.SUPPLEMENTAL FILE 2, XLSX file, 0.04 MB.SUPPLEMENTAL FILE 3, XLSX file, 0.03 MB.

ACKNOWLEDGMENTSThe research presented here was supported by CRG funding URF/1/2982-01-01 from

King Abdullah University of Science and Technology (KAUST) awarded to P.-Y.H. A.K.,C.M., and K.Y.C. thank KAUST and CSIRO Land and Water for financial support.

We thank Lina Marcela Silva Bedoya, Silvia Salgar Chaparro, Erika Suarez Rodriguez,Benjamin Tuck, and Katelyn Boase from the Curtin Corrosion Centre at Curtin Universityfor the warm hospitality and their support.

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