Peptide-Based Fluorescent Biosensing for Rapid Detection of FuelBiocontaminationOksana M. Pavlyuk† and Oscar N. Ruiz*,‡

†Environmental Microbiology Group, University of Dayton Research Institute, University of Dayton, Dayton, Ohio 45469, UnitedStates‡Fuels and Energy Branch, Aerospace Systems Directorate, Air Force Research Laboratory, Wright-Patterson AFB, Ohio 45433,United States

*S Supporting Information

ABSTRACT: To reduce the impact of biodeterioration in fuel systems, effective methods for early detection and monitoring ofmicrobial growth in the fuel are required. This study presents the development of broad-range peptide biorecognition elements(BREs) that target cell surface determinants produced by hydrocarbon-degrading microorganisms during growth in fuel. BREswere used to biofunctionalize fluorescent semiconductor particles (quantum dots, QDs) to produce a sensitive quantitativefluorescence-based assay for detection of microbial growth in fuel. A biopanning method in the presence of fuel was used toselect phage-displayed heptameric peptide BREs against epitopes conserved in fuel-degrading Gram-negative bacteria includingPseudomonas spp. and Acinetobacter spp. Fluorescence microscopy analysis and fluorescence signal measurements relative tocolony-forming units (CFUs) demonstrated the binding and specificity of the BRE-QDs for fuel-degrading Gram-negativebacteria. Cross-reactivity with Gram-positive bacteria Arthrobacter and Lysinibacillus was not observed. The assay was shown to bespecific for detection of Gram-negative bacteria. Jet fuel samples amended with different concentrations of fuel-degrading bacteriawere used to determine the sensitivity and limit of detection (LOD) of the assay; an LOD of 5 × 104 colony forming units(CFUs) with detection levels as low as 5 × 103 CFUs was established for the best performing BRE−QD conjugate. The peptideBRE−QD chemistry effectively detected biocontaminated fuel samples from fuel tanks. The peptide BREs may serve tobiofunctionalize various fluorescent, chemiluminescent, and colorimetric molecules as well as optical and electrical transducers todeveloped effective biosensors for detection of microbial contamination in fuel.

Microbial contamination of fuel presents a significantproblem for both military and civilian applications due

the deterioration of fuel quality and subsequent long-termconsequences including reduced fuel stability, tank corrosion,filter plugging, injector fouling, deactivation of fuel-watercoalescers, and coating degradation.1−13 Thus, effective monitor-ing of fuel quality and prevention of microbial growth in the fuelis of great importance as a cost-saving strategy that serves toprolong the performance and lifetime of the fuel system.However, current tests are costly, and in many cases, must beperformed by highly trained scientists at off-site laboratoriesrequiring the shipment of fuel samples, culturing microbes, andlong wait times. Even when sophisticated molecular-basedtechniques such as quantitative real-time polymerase chainreaction (qPCR) and DNA sequencing are used, having toextract DNA from the fuel for analysis is a difficult task. Also,DNA-based tests cannot differentiate between live and deadmicroorganims.14 Often, commercially available field tests havelow accuracy and at best provide semiquantitative results. Sometest kits require growing microorganisms for days to visualizethem or rely onmeasuring adenosine triphosphate (ATP), whichis a labile molecule of variable abundance depending on themicrobial growth stage. Antibody-based detection methods arefrequently affected by degradation and are negatively influencedby the presence of fuel. Overall, biodeterioration is oftendetected only after the normal operation of the fuel system hasbeen impacted, requiring expensive remediation.

The first step toward the development of a simple biosensingmethod capable of detecting microorganisms in fuel is to developa functional biorecognition element (BRE) that can detect largegroups of fuel-degrading microorganisms. The Gram-negativebacteria group is highly diverse and considered a predominantgroup of fuel biocontaminants. Thus, development of a broad-spectrum BRE for detection of Gram-negative bacteria is highlydesirable. BREs can be short nucleic acid-based aptamers orpeptides that mimic antibody−antigen interactions, which can beeasily obtained by well-established high-throughput screeningmethods such as systematic evolution of ligands by exponentialenrichment (SELEX)15,16 and phage display.17,18 In this regard,small 7−12 amino acid (aa) peptides are ideal BREs withnumerous advantages over other molecular probes, includinghigh chemical diversity, ease of synthesis and conjugation to thesurface of the signal transducer, and high stability in harshenvironments like fuel.19 Peptide BREs share the high affinityand specificity of antibody−antigen binding, but unlike antibod-ies, short peptides do not require immunogenic antigens andpost-translational modifications such as disulfide bonds, and theyare not prone to batch variation because they are chemicallysynthesized. Unlike large multidomain proteins and antibodies,peptide molecular probes are not prone to denaturation, have

Received: December 15, 2016Revised: March 4, 2017Published: March 6, 2017

Article

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© 2017 American Chemical Society 3747 DOI: 10.1021/acs.energyfuels.6b03350Energy Fuels 2017, 31, 3747−3758

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longer shelf life, and potentially can be reused. Chapleau et al.20

showed that shorter single-domain antibodies, also known asnanobodies, were able to retain antigen binding activity in thepresence of jet fuel. Finally, peptides can be easily conjugated toreporter fluorescent, chemiluminescent, and colorimetric mole-cules and signal transducing nanomaterials for simple detectionof the target without altering the antigen-binding capacity andbiorecognition activity of the BRE.Fluorescent semiconductor nanoparticles, more commonly

known as quantum dots (QDs), have established themselves assuperior alternatives to traditional chemical dyes in terms ofbrightness and stability against photobleaching.21−23 Moreover,their broad absorption spectra allow for utilization of a singleexcitation source, and their narrow symmetrical emission spectracombined with size-dependent quantum yields and large Stokesshifts make quantum dots excellent reporter fluorophores formultiplexed detection of different microorganisms.24−30

Many species of bacteria are known to contaminate fuel.6,9,31,32

From the prokaryotes, the Gram-negative bacteria, including thenotoriously difficult to eradicate Pseudomonas, are predominantin biocontaminated fuel.32−34 Persistence of P. aeruginosa andother Pseudomonas species in the harshest environments isbelieved to be due in part to the low permeability of outermembrane proteins (porins) and the presence of effluxtransporter proteins (efflux pumps) that extrude xenobiotics,thus allowing these bacteria to proliferate in antimicrobial drugs,hydrocarbons, and fuel.34,35 For instance, OprF is a major porinof P. aeruginosa responsible for outer membrane permeabilityand nonspecific diffusion of small polar nutrients across thebacterial membrane and has also been implicated in otherimportant physiological functions.36 Specifically, OprF wasdemonstrated to serve as a connector between the outer andinner membranes, and deletion of OprF produces an unstableouter membrane and aberrant cell morphology.37 The 326 aa-long OprF consists of 15 transmembrane motifs comprising theβ-barrel and 8 highly conserved extracellular loops38 that havebeen used as target epitopes for the development of Pseudomonasaeruginosa specific antibodies.39 The secondary structure of OprFregulates its permeability by adopting an open or a closedconformation depending on the cell requirements. Additionally,OprF is thought to be a modulator of quorum sensing andenhanced bacterial virulence, and importantly, OprF expressionis involved in the formation of anaerobic biofilms.40,41 It wasrecently demonstrated that OprF was involved in the uptake ofaromatic solvents including toluene,42,43 and is regulated at thetranscriptional level by hydrocarbons.34 OprF is immunogenicand highly conserved in Pseudomonads.44,45 Therefore, OprF canbe used as a biomarker to detect Pseudomonas species and otherfuel-degrading Gram-negative bacteria with structurally con-served OprF protein for effective monitoring of fuel quality.Similarly, the outer membrane protein Opr86, which is highly

conserved in Gram-negative bacteria, was shown to be essentialin outer membrane biogenesis.46 Opr86 is responsible for theassembly and insertion of β-barrel outer membrane proteins intothe outer membrane via complex formation with otherlipoproteins.46 Antibodies against Opr86 prevented biofilmformation by P. aeruginosa PAO1.46 Organic solvents47 andfuel34 were shown to up-regulate the expression of Opr86.Conveniently, the amino acid composition and structure ofP. aeruginosa Opr8646,48 and OprF39 are known, thus allowingutilization of some of the extracellular loop motifs as targetepitopes for isolation of peptide BREs.

In the present study, conserved extracellular loop epitopes ofOprF andOpr86 outer membrane proteins were used as antigensto isolate binding biorecognition elements from a peptide libraryusing phage display in the presence of fuel. The synthetic peptidecounterparts of the selected heptameric peptides weresubsequently used to biofunctionalize quantum dot (QD)reporter fluorophores. The resulting peptide BRE-QD con-jugates were used as labeling reagents in a lateral assay for thequantitative detection of Gram-negative fuel-degrading bacteriain the presence of fuel. The assay specificity and limit of detectionwere determined, and its application for detection of bacteria incontaminated fuel samples from field tanks was demonstrated.

■ RESULTS AND DISCUSSIONSelection of Heptapeptide Biorecognition Elements

(BREs) in the Presence of Fuel. The structure of Pseudomonasaeruginosa major outer membrane protein OprF was elucidatedin a previous study.39 The 326 amino acids(aa)-long OprFconsists of a 15 motif transmembrane domain and 8 extracellularloops.38 While multiple extracellular loops were shown to beimmunogenic, the epitope of sequence GTYETGNKKVH wasshown to be most reactive for the production of monoclonalantibodies.39 The knowledge of the secondary structure of OprFand the great level of conservation across different Pseudomonasspecies was used as the basis for the selection of the 11 aa-longGTYETGNKKVH (amino acids 55−65 of OprF, and denoted asOprF1 in this study) extracellular loop as the target epitope forselection of BREs using phage display biopanning in the presenceof fuel.AnOprF1 synthetic peptide biotinylated at theN-terminal was

used for solution biopanning screening of a commerciallyavailable M13 bacteriophage library displaying heptamericpeptides at the N-terminal of the P3 coat protein. The advantagesof solution-phase biopanning include the availability of all theOprF1 amino acid residues for interaction with the potentialpeptide binders and lesser likelihood of isolating unspecificpeptides that might bind to the capture element used to purifythe phage−antigen complex (i.e., magnetic or protein G beads).OprF1−phage complexes were captured with streptavidin-coated magnetic microbeads, eluted and amplified in E. coli foruse in subsequent rounds of selection biopanning. After eachround of selection, the DNA of multiple phage isolates carrying asingle heptapeptide biorecognition element (i.e., monoclonalphages) was sequenced to determine the amino acid sequencesof the OprF-binding peptides (OBPs). After four rounds ofselection, the phage pool was enriched for OprF1-binding phageswith three consensus sequences (Supporting Information TableS1), and a predominant PPKINIM peptide with 80% abundancebased on round 4 clones. Unfortunately, this type of bindingprofile is characteristic of what is known as a “library collapse”,49

where the loss of library diversity is a result of enrichment forbacteriophages displaying nonspecific peptides that conferadvantageous growth properties including more efficientinfectivity and phage assembly/extrusion from the bacterialhost cell. This phenomenon was further confirmed when theround 4 phage pool was used as an input phage for the next roundof biopanning in nonphysiological conditions at pH 8.5 and inthe presence of 1% v/v Jet A fuel in Bushnell−Haas (BH)minimal media. These biopanning conditions were chosen tomimic the fuel tank milieu, where the fuel-degrading bacteriawould ultimately be detected.3 Interestingly, under theseconditions the binding of library phage selected so far wascompletely abolished, and only wild-type M13 was isolated after

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round 5 (data not shown). This observation indicated thatselective pressure other than multiple rounds of biopanning andamplification must be applied to isolate OprF1-specificbacteriophages lacking growth advantages. To achieve thisgoal, BH minimal media supplemented with 1% v/v Jet A atnonphysiological pH (pH 5.5 or pH 8.5) was used for all roundsof biopanning and removal of nonbinding phages. Using theseconditions, the profile of OprF-binding peptides (OBPs)changed dramatically (Figure 1) and many additional peptidebinders were identified (Supporting Information Table S2 andS3). The M13 bacteriophage was shown to survive innonaqueous solvents and at acidic/basic pH’s that mimickedfuel tank conditions. Interestingly, if fuel was not added (Figure1a and Table S3) or the pH was changed back to thephysiological pH of 7 (Figure 1b and Table S2), the phagelibrary converged back to the PPKINIM peptide, obliterating theselection of phages displaying the OprF1-specific peptides andlacking advantageous growth properties. Furthermore, since thelibrary collapse is a direct consequence of amplification in E. coli,this step was omitted in order to determine a more accuratepercentage of abundance that would be reflective of the bindingaffinity of OprF-binding peptides (Supporting InformationTable S4). Fourteen monoclonal OprF1-binding phages fromthe third selection round were combined at equal concentrationsin Bushnell−Haas pH 8.5 supplemented with 1% v/v Jet A andincubated with biotinylated OprF1, followed by alternativewashes with Bushnell−Haas pH 8.5 or pH 5.5 supplementedwith Jet A. Eluted unamplified phages were titered, and 30randomly selected clones were used to determine percent

abundance and thus relative affinity for OprF. Not surprisingly,using these conditions, the relative percent abundance ofPPKINIM clone was determined to be only 3%, in stark contrastto the 80% abundance under physiological conditions. Finally,the phage library was screened to identify target-unrelatedpeptides50 by using biotinylated BSA as a target for biopanning.In addition to the PPKINIM phage, another bacteriophagedisplaying the IQTNPTM peptide was found to cross-react withBSA (Supporting Information Table S5). Collectively, stringentbiopanning and library screening allowed us to select six uniqueheptapeptides for fluorescent probe synthesis and evaluation ofbacterial detection (Table 1).The binding of multiple BREs (i.e., OBP 4 throughOBP 12) to

the OprF1 peptide was initially assessed byWestern blot analysis.

Figure 1. Selection of OprF-binding peptides BREs via biopanning in fuel tank conditions. An M13 phage library (1 × 1011 pfu/ml) in Bushnell−Haas(BH) pH 8.5 (a) or pH 5.5 (b) supplemented with 1% v/v Jet-A was incubated with biotinylated OprF1 target antigen, and the selected phages wereamplified, and the DNA of 15 randomly picked clones per round of selection was sequenced to determine the amino acid composition of OprF-bindingpeptides. (a) OprF-binding peptide distribution as a function of fuel additive. After selection round number 4, the binding and washing conditions wereadjusted to contain BH at pH 8.5 without fuel to monitor changes in peptide binding profile. (b) OprF-binding peptide distribution as a function of pH.After selection round number 4 with fuel and pH 5.5, the binding and washing conditions were adjusted to BH pH 7 with 1% Jet-A, and the change inpeptide binding profile was monitored.

Table 1. OprF-Binding Peptides (OBPs) and Their InitialScreening for Binding to P. stutzeri

PeptideID

PeptideSequence pIa

%Abundanceb

Fluorescence(RFU)c

OBP4 RRSNSQL 12.0 33 4520 ± 473OBP6 NMTNPPP 5.5 10 2080 ± 280OBP7 QITLRST 9.8 10 2625 ± 543OBP9 QMLLRLP 9.8 3 3338 ± 590OBP11 PIKTNRK 11.2 10 5308 ± 501OBP12 PKRTPRH 12.0 3 6443 ± 957

aTheoretical pI calculated using web.expasy.org. bCalculated based on30 randomly picked clones from the unamplified phage pool. cRelativefluorescence units for OBP-QD525conjugates.

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Monoclonal OprF-specific bacteriophages were incubated withbiotinylated OprF1 (OprF1-B) peptide epitope under con-ditions similar to those used in biopanning. The resulting phage−OprF1-B complexes were recovered using streptavidin-coatedmagnetic beads, and the phage−OprF1-B complexes wereresolved via SDS-PAGE, and detected by Western blot usingantibodies against the M13 phage capsid and the biotin moleculeattached to OprF1. The results showed that monoclonal OprF-specific phages bound specifically to OprF1-B, and both thephage and OprF1-B were detected in immunoblots (Figure 2).

When phages with specificity for bovine serum albumin (BSA)were used against the OprF1-B target, a significant signal was notdetected in the immunoblots (Figure 2). This result confirmedthat complexing specificity was due to the OprF1-specificpeptides and not caused by nonspecific binding of M13 phagecapsid and nonspecific library peptides.Having established an effective biopanning protocol with

OprF to select BREs against Pseudomonads, the procedure wasapplied to develop BREs with broader specificity to detectmultiple Gram-negative genera. To achieve this, the Opr86 outermembrane protein was targeted. The Opr86 external loopfragment spanning amino acid residues 668 to 683 was shown tobe a highly immunogenic epitope that could be used in theisolation of Pseudomonas specific antibodies.46 Moreover, aminoacid sequence alignment analysis performed with PRofileALIgNEment (PRALINE)51 on the Opr86 external loop regionspanning amino acids 630 to 665 from different Gram-negativespecies revealed the region consisted of 35 highly conservedamino acid residues presenting more than 86% sequencehomology among several Pseudomonas species (Figure 3a), andmore than 50% sequence homology among various Gram-negative bacteria (Figure 3b). Thus, the particular region of theOpr86 extracellular loop of sequence YGSTDGLPFY-ENYYAGGFNSVRGFKDSTLGPRSTP was chemically synthe-sized with a biotin capture element and used as target epitope forBRE development in solution biopanning in Bushnell-Haas pH8.5 supplemented with 1% Jet-A. Following the previouslyestablished procedure for OprF, several unique Opr86 peptideBREs (OPPs) able to detect bacteria were identified after threerounds of selection (Table 2).Screening of Peptide BRE−Quantum Dot Conjugates

Activity. OprF1- and Opr86-binding peptides (OBPs and

OPPs, respectively) modified with a C-terminal 3-glycine pluscysteine (GGGC) linker were cross-linked to amine-function-alized quantum dots (QD525) via succinimidyl iodoacetate(SIA) following the manufacturer’s protocol. Several importantfactors have influenced the selection of a reporter fluorophore forour studies. For example, in addition to their tunable opticalproperties and exceptional brightness, quantum dots (QDs)were suitable for peptide functionalization due to their size andthe number of sites available for conjugation. Quantum dots aremuch larger than traditional chemical fluorophores, withdiameter in the range 10−20 nm, and this size proximity tobiological molecules makes them more suitable for bacteriallabeling. In addition, the quantum dots used in this study werecoated with multiple amine functionalities (exact number variesfrom batch to batch), thus allowing functionalization withmultiple peptide copies, in contrast to the one peptide per onechemical fluorophore as is the case of traditional fluorescent dyes.This is particularly important in order to circumvent a possiblereduction in binding affinity of a peptide-dye for the target as aresult of avidity loss from the pentavalently phage-displayedpeptide arrangement. The emission peak fluorescence at 525 nmof 1 × 109 P. stutzeri cells labeled with peptide BRE−QD525

Figure 2. Western blot analysis of OprF-specific biorecognitionelements. Western blotting was performed by incubating thebiotinylated OprF1 peptide epitope with monoclonal OprF-specificbacteriophages (lanes 1−6: OBPs 4 thru 12) and capturing the resultingcomplexes with magnetic streptavidin beads, followed by SDS-PAGE,transfer to a PVDF membrane, and immunoblotting with M13 andbiotin-specific antibodies. Protein bands were visualized with an alkalinephosphatase-conjugated secondary antibody. Bovine serum albumin-specific bacteriophage (BBP2, lane 7) was used as a negative control todemonstrate that nonspecific binding of phages to OprF1 epitope wasnot occurring. Biotinylated OprF1 (OprF1-B) and wild type M13 phagewere used as positive controls for the respective antibodies used.

Figure 3. Opr86 sequence alignment. Multiple alignment of UniProtprimary amino acid sequences was performed with PRofile ALIgNE-ment (PRALINE). The color scheme of the alignment is based onamino acid position conservation assigned by the PRALINE scoringscheme (0 for the least conserved alignment position and 10 for themost conserved). (a) Opr86 alignment with Pseudomonas spp.; (b)Opr86 alignment with various Gram-negative bacteria. Note the keyamino acids highly conserved (9−10/10) in both Pseudomonas spp. andother Gram-negative bacteria (Pro637, Ala644, Gly645, Gly646, Val650,Arg651, Gly652, Phe/Tyr653, Leu/Ile658, Gly659, Pro660, Arg/Lys661).

Table 2. Opr86-Binding Peptides (OPPs) and Their InitialScreening for Binding to P. stutzeri

PeptideID

PeptideSequence pIa

%Abundanceb

Fluorescence(RFU)c

OPP1 PRIRKSH 12.0 3 12258 ± 2060OPP2 MHNLNLL 6.5 2 1847 ± 52OPP3 LPSTIHR 9.8 2 2251 ± 63OPP4 LRPLMNR 12.0 3 1383 ± 74OPP5 IITMKRR 12.0 3 4408 ± 225OPP6 RKKSRIR 12.3 2 4126 ± 98

aTheoretical pI calculated using web.expasy.org. bCalculated based on30 randomly picked clones from an unamplified phage pool. cRelativefluorescence units for OPP-QD525 conjugates.

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Figure 4. continued

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conjugates was measured in a fluorometer, and their relativefluorescence units (RFU) were compared (Table 1 and 2).Peptides OBP11 and OBP12 targeting OprF, and peptide OPP1targeting Opr86 presented fluorescence levels that greatlysurpassed the other selected peptides for the respective target(Table 1 and 2). Thus, OPP1, OBP11, and OBP12 were selectedfor further characterization and validation. During the use ofQD525, a small interfering peak at 520 nm caused by cellautofluorescence was observed. To prevent any contributionfrom cell autofluorescence to the overall emission from BRE-QDlabeled cells, we chose to use QD545 in all further experimentsand assay validations; the QD545 with fluorescence emission at545 nm wavelength did not present an interfering peak.Characterization of Peptide−Quantum Dot Conju-

gates Specificity for Gram-Negative Bacteria. To charac-terize the specificity of the peptide−QD545 conjugates for the

intended bacterial groups, fluorescence imaging and fluorometricanalysis were performed using different Gram-negative andGram-positive fuel-degrading bacteria. 1 × 109 cells of Gram-negative bacteria, P. stutzeri, P. alkaligenes, P. aeruginosa, andAcinetobacter venetianus, and Gram-positive bacteria, Arthrobactersp. and Lynsinibacillus sp., were labeled with OPP1−QD545,OBP11−QD545, and OBP12−QD545, visualized using fluo-rescence microscopy (Figure 4a−b), and the fluorescence wasquantified using a fluorometer (Figure 4c). The fluorescencemicrographs showed that OPP1, OBP11, and OBP12 specificallylabeled the Gram-negative bacterial species, but not the Gram-positive bacteria, which do not express OprF and Opr86 outermembrane proteins. The presence of a high number of bacteria inall treatments was confirmed by bright field imaging (Figure 4a−b). To confirm that QDs without biofunctionalization did notbind to the bacteria cells, all bacterial species were exposed to

Figure 4. Fluorescence imaging and fluorometry of fuel-degrading bacteria labeled with OprF and Opr86 binding peptides conjugated to QD545.Bacterial pellets corresponding to 1× 109 cells were labeled with 1.5 μMpeptide−QD545 for 30min at r.t., washed 3×with PBS, and resuspended in 0.5mL of PBS for fluorescence measurements; 10 μL aliquots were used for imaging. (a) Fluorescence imaging of Gram-negative bacteria (Acinetobactervenetianus and Pseudomonas spp.) using peptide−QD545 conjugates. (b) Fluorescence imaging of Gram-positive bacteria labeled with peptide−QD545conjugates. (c) Fluorometry of A. venetianus and Pseudomonas spp. labeled with peptide−QD545 conjugates. P < 0.05 (*); P < 0.01 (**); P < 0.001(***).

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QD545 at a concentration equal to the concentration of peptideBRE−QD545 conjugates used in testing. The results showed alack of bacterial fluorescence from the QD545 treatment andfrom the unlabeled cells used as negative control (Figure 4a−b).Careful analysis of the fluorescence micrographs indicated thatonly the cell wall of Gram-negative bacteria was fluorescentlystained (See inset for P. alkaligenes in Figure 4a, and Figures 5 and6a). Labeled cells appeared dark in the center with highlyfluorescent outer membranes indicative of colocalization of thepeptide BRE-QDs with OprF and Opr86 at the cell wall (Figure6a). Also, the fluorescence level of each sample was measured viafluorometry (Figure 4c). Unlabeled cells and cells exposed tononbiofunctionalized QDs only presented background levels offluorescence below 25 RFU; samples without cells did notfluoresce. The OPP1-QD was tested and shown to recognize 18different Gram-negative bacteria (Table 3). This indicated thatOPP1 BRE may serve as a probe for broad detection of Gram-negative bacteria. Both OBP11 and OBP12 provided gooddetection of Pseudomonads (Figure 4c). However, OBP11 andOBP12 provided unexpected high fluorescence with P.alkaligenes and P. stutzeri, respectively (Figure 4c). The higherfluorescence observed with OBP11 and OBP12 may have beenthe result of increased affinity of these two peptide BREs for theOprF epitope present in P. alkaligenes and P. stutzeri.Interestingly, it was observed that biofilms produced by

Pseudomonas species, especially noticeable in the P. aeruginosa

fluorescence micrograph (OPP1 panel of Figure 4a), were alsolabeled in addition to the planktonic cells (Figure 4a). Fuel-degrading bacteria such as Pseudomonas produce biofilms,especially at the fuel−water interface, to protect against thetoxic fuel environment and increase their access to thehydrocarbons in the fuel.34 It has been indicated that extracellularpolymeric substance (EPS), also known as extracellular matrix(ECM), can become an important barrier that impedes thepenetration of molecules such as antibiotics and antimicrobials tocells residing within biofilms. However, several reports indicatethat nanoparticles, including QDs, can be modified with specificligands and functional groups to increase penetration into EPSand biofilms, and even permeate into cells, tumors, and theblood−brain barrier.52−54 Recently, Li et al.55 showed thathydrophilic and hydrophobic QDs can be functionalized withpositively charge ligands to increase penetration into the biofilm;a similar result was not observed with neutral and negativelycharged ligands. Our results showed the peptide BRE-QDspenetrated the biofilm, staining cells residing deep in the biofilm(Figure 5). Biofilm penetration may have been aided by themultiple positively charged amino acids, such as lysine (K),arginine (R), and histidine (H), present in the peptide BREs, aswell as the amine group connecting the SIA-QD to the peptide.The ability of the peptide BRE-QD conjugates to bind and labelplanktonic cells and cells in biofilms increases the applicability ofthe assay for detection of bacteria in fuel systems.

Figure 5. Fluorescence imaging of P. stutzeri biofilm labeled with 1.5 μMOPP1-QD545 conjugate. (a) 40× bright field, (b) 40× fluorescence, (c) 100×fluorescence.

Figure 6.Detection of Gram-negative bacteria in fuel samples amended with bacteria using peptide-QD545. (a) Fluorescence micrograph (100×) of P.stutzeri cells labeled with peptide biofunctionalized quantum dots. Notice the cell membrane was preferentially labeled. (b) Limit of detection of P.stutzeri cells extracted from 1L of Jet A fuel in 1 mL of bacterial recovery solution (BRS). (c) Limit of detection of A. venetianus cells extracted from 1L ofJet A fuel in 1 mL of BRS.

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Detection of Bacteria in Fuel Using the Peptide BRE-QDChemistry.To test the applicability of the peptide BRE-QDchemistry in the detection of bacteria in fuel and characterize thelimit of detection (LOD) in such a system, an assay wasdeveloped to recover, label, and detect bacterial cells from 1 L jetfuel samples (see Material and Methods). The results showedthat bacteria were efficiently labeled as indicated by detection ofhigh fluorescence levels emanating from the cell wall underfluorescence microscopy (Figure 6a). The LOD was reliablydetermined from assays performed by multiple testers. TheOPP1−QD545 conjugate detected P. stutzeri and A. venetianus atan LOD of 5 × 104 CFU/mL of bacterial recovery solution(BRS), and detection was sometimes possible down to 5 × 103

CFU/mL. OBP11−QD545 and OBP12−QD545 presented aLOD of 5 × 105 CFU/mL of BRS for P. stutzeri and A. venetianuswith detection sometimes possible down to 5 × 104 CFU/mL.This indicated that the assay had the potential to be furtheroptimized to detect much lower bacterial levels in fuel.Differences in LOD between OPP1 and the two OBPs could

have been attributed to variability in Opr86 and OprF proteinlevels in the different bacterial strains, as well as structural andconformational differences in the external epitopes of Opr86 andOprF that may modulate the binding of BRE to the targetepitope. Intrinsic variability in how the assay protocol wasperformed by the different testers and the use of multiplecentrifugation steps in the protocol was credited for the detectionfluctuations at cell levels below the reproducible LOD, and fornot achieving an even lower LOD. Currently, we are furtherdeveloping this assay by substituting centrifugation steps with theuse of a single filter membrane to recover cells from the fuel,carryout all washes, and perform the detection step. We expectthis change will prevent the loss of labeled bacteria, reducebackground fluorescence, and improve the assay LOD.

Tests performed to understand the behavior of thefluorescence signal emanating from different concentrations ofP. stutzeri cells labeled with OBP11-QD545 and OBP12-QD545showed the fluorescence intensity changed as a power functionwith respect to cell level (Figure 7). The fluorescence decay

model for each peptide BRE-QD could be used to estimate celllevels in samples directly from the fluorescence signal readouts.Future refinement of these models should allow quantitativedetermination of the cell concentration in unknown samples.The ultimate goal of this study was to use the peptide BRE-QD

chemistry and the developed test method to detect micro-organisms in potentially contaminated fuel samples from thefield. To test if the peptide BRE-QD chemistry could effectivelydetect bacteria in a fuel sample from the field, a contaminated jetfuel sample from a fuel tank was obtained. One milliliter of thewater layer from the fuel sample (Figure 8a) was tested withOBP11, OBP12, and OPP1 BRE-QDs following the describedprotocol (see Material and Methods). The fluorometer readoutsindicated very high levels of fluorescence with all three peptideBRE-QD assays that ranged from 22,000 RFU and 37,000 RFU(Figure 8b−c). The high fluorescence levels detected were anindication of heavy bacterial contamination in the fuel sample.Using the fluorescence decay model of OBP11 and OBP12, a cellconcentration between 7 × 106 and 4 × 107 CFU/ml wasestimated. To confirm that bacteria was actually present in thefuel sample, the bacterial contamination level was determined by

Table 3. Fluorescence Response of Different Gram-NegativeBacteria Species Labeled with OPP1-QD525a

Gram-Negative Bacteria RFU 525 nm

Pseudomonas aeruginosa PAO1 20,000Pseudomonas aeruginosa ATCC33988 30,000Pseudomonas alkaligenes 63,000Pseudomonas f rederiksbergensis 10,000Pseudomonas putida 4,600Pseudomonas stutzeri 33,000Escherichia coli ER2738 80,000Acinetobacter venetianus ATCC31012 17,000Achromobacter sp. 25,000Alkaligenes faecalis 32,000Enhydrobacter sp. 87,000Ralstonia picketti 15,000Chryseobacterium hispalense 80,000Stenotrophomonas maltophilia 13,000Marinobacter hydrocarbonoclasticus 100,000Rhodovulum sp. 64,000Methylobacterium sp. 43,000Alkanivorax borkumensis 80,000

Gram-Positive Bacteria RFU 525 nmArthrobacter sp. no signalLysinibacillus sp. no signal

aCells were recovered from 1 mL of 1 O.D. bacterial culture. RFU:relative fluorescence unit.

Figure 7. Characterization of the fluorescence signal profile of labeledcells. 1 × 109 P. stutzeri cells were labeled with (a) 1.5 μM OBP11-QD545, and (b) 1.5 μMOBP12-QD545 and then diluted from 1 × 105

to 1 × 107 to determine the fluorescence signal intensity at different cellconcentrations. The exact cell number in each labeled sample wascharacterized by the plate colony counting method to provide the CFUs.

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quantitative real-time PCR (qPCR), a nucleic acid-basedmolecular method, and using the bacterial plate count method.The qPCR method, which can detect both culturable, non-culturable, and free DNA, detected 1.5 × 106 bacterial 16S genecopies/mL; this level of contamination is considered high.Colony counts, which quantify only the culturable bacteria,detected about 80 CFU/mL. While the level of culturablebacteria appeared to be lower than expected from the qPCR test,it is well-known that bacteria adapted to the fuel environmentmay not form colonies in culture without prior acclimatization,and many environmental bacteria are nonculturable. DNAsequencing of a 500bp region of the bacterial 16S rrn geneidentified the isolated bacteria as Pseudomonas aeruginosa, whichlater was confirmed to degrade hydrocarbons in the laboratory.The cell concentrations predicted from the RFU values ofpeptide-labeled cells are in general agreement with the leveldetected by the well-established qPCR method. This indicatedthe peptide BRE-QD chemistry and the established test methodare suitable for detection and estimation of Gram-negativebacteria in fuel samples.

■ CONCLUSION

In the present study, we have performed phage display innonphysiological biopanning conditions with variable pH and jet

fuel as an additive to isolate peptide biorecognition elementsspecific for OprF and Opr86 outer membrane proteins ofPseudomonas and Gram-negative bacteria. Using establishedtechniques, quantum dots were biofunctionalized with peptideBREs, and evaluated for recognition and binding to Gram-negative bacteria such as Acinetobacter venetianus and severalPseudomonas spp. In contrast, no Gram-positive bacteria weredetected, demonstrating the selectivity and specificity of peptideBREs. Overall, peptide-biofunctionalized quantum dots weredemonstrated to efficiently label fuel-degrading Gram-negativebacteria in a simple test method that allowed detection in realtime. The method detected bacteria in contaminated fuelsamples from the field, which further supported its applicabilityas a field test. Improvements in the reported assay methodology,including a more efficient bacterial fuel extraction step andpreventing loss of cells during the wash steps, are currentlyunderway, and these are expected to further improve the limit ofdetection (LOD) and the field applicability of the assay. The goalof this study was to demonstrate that it was possible to developbroad-spectrum peptide biorecognition elements for detection oflarge microbial groups. Currently, we are working on theselection of peptides with broad specificity for Gram-positivebacteria, and fuel-degrading yeast and filamentous fungi. Onceproduced, these new broad-range peptides can be combined with

Figure 8.Detection of biocontamination in a jet fuel sample from a fuel tank. (a) The aqueous phase of a contaminated Jet A fuel sample was separatedfrom the organic phase, and a 1 mL aliquot was centrifuged at 10,000g for 5 min. Supernatant was removed and the cell pellet was labeled with 1.5 μMofpeptide-QD545-peptide (or QD alone) in PBS. The labeled cell pellet was resuspended in 0.5 mL of PBS, and the fluorescence was measured (c). Thesample was serially diluted and plated to determine CFUs (b).

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the Gram-negative peptide BREs to development a multiplexdetection assay. The developed peptide BREs could be applied inthe fabrication of novel biosensors through the biofunctionaliza-tion of optical and electrical transducer nanomaterials.

■ MATERIALS AND METHODSBacterial Cultures and Methods. Pseudomonas aeruginosa

ATCC33988 and Acinetobacter venetianus ATCC31012 were purchasedfrom the American Type Culture Collection (Manassas, VA). P. stutzeri,P. alcaligenes, Arthrobacter sp., and Lysinibacillus sp., plus 12 otherbacteria shown in Table 3 were isolated in our laboratory from fuel-contaminated soil and water, and stored in 15% glycerol at −80 °C. TheP. aeruginosa PAO1 strain refers to the human pathogenic type strain.Escherichia coli 2738 was used from the commercially available phagedisplay kit (New England Biolabs, Ipswich, MA). Overnight cultures offuel-degrading and environmental bacteria were grown in Luria−Bertani(LB) broth at 28 °Cwith shaking at 225 rpm, and E. coli grown at 37 °C.Biopanning of Phage-Displayed Peptides. Solution-phase

biopanning was carried out as described by the manufacturer (NewEngland Biolabs, Ipswich, MA) with some modifications, includingchanging the pH from 7.0 to 5.5 and 8.5, and adding 1% v/v of Jet A fuel.The first round of selection was carried out by diluting the Ph.D.-7bacteriophage library 100-fold in 0.1% Tris buffer saline plus Tween 20(0.1%TBST) at the appropriate pH for selection plus fuel. Subsequently,the phage library was incubated with 1 μg of N-terminal biotinylatedtarget protein fragment (either OprF1: GTYETGNKKVH, OprF2:ADIKNLADFMKQYPSTSTT, Opr86: YGSTDGLPFYENYYAGGF-NSVRGFKDSTLGPRSTP) for 1 h at 25 °C. Phage−protein complexeswere captured with 50 μL of streptavidin magnetic microbeads, and thepelleted sample was washed 10 times with 1 mL of 1× TBS plus 0.05%Tween 20 buffer (TBST) to remove unbound and weakly bound phageparticles. Bound bacteriophages were eluted from the beads by loweringthe pH (0.2 M Glycine-HCl pH 2.2) while rotating gently for 10 min at25 °C. After neutralization with 1 M Tris-HCl pH 9.1, eluted phageswere amplified by infection of E. coli strain ER 2738 grown in LBmedium until early log phase (OD600 0.1−0.5). The amplified phagepool was isolated by precipitation with PEG/NaCl and titered todetermine the phage concentration for the next round of selection; thetiter of the amplified phage (≥1010 pfu/mL) was determined byinfecting E. coli ER2738 cells and subsequently selecting the infectedcolonies, producing a blue color in X-gal/IPTG-containing selectivemedia. Amplified phages from round 1 were precleared withstreptavidin-coated magnetic microbeads (50 μL) to further removenonspecific binders and were then used as the input phage for round 2 ofselection. Enrichment of the bacteriophage pool was achieved byperforming 4 rounds of selection under the appropriate pH plus jet fuelconditions. After each round of selection, the genomic DNA fromindividual phage clones was sequenced by GenScript (Piscataway, NJ).Western Blot Analysis. Western blotting was performed by

preparing a 200 μL solution with each of the phage clones at aconcentration of 1× 1011 pfu/mL in 1X Tris buffer saline (TBS) pH 7.5.Then, 10 μL of OprF1-biotin target peptide of concentration 1 mg/mLwas added to each phage solution, followed by incubation at 25 °C for 1h. Phage-OprF-biotin complexes were captured and pulled-down with25 μL of streptavidin-coated beads, and the captured complexes werewashed 5 times with 1X TBST. The pelleted complexes were finallyresuspended in 20 μL of 2X Laemmli buffer, heated to 95 °C for 5 min,and resolved in a 14% SDS-PAGE gel. Proteins were blotted to anitrocellulose membrane, and blocked with TBST containing 5% BSA.To detect phages, a 1:2000 dilution of rabbit anti-M13 phage antibody(primary antibody) followed by a 1:5000 dilution of alkalinephosphatase (AP)-conjugated goat antirabbit antibody was used. Fordetection of biotinylated OprF1, a 1:2000 dilution of AP-conjugatedgoat antibiotin antibody was used. For colorimetric visualization, BCIP/NBT reagent was used. Ten μL of 9 × 1012 pfu/mL of wild type M13phage in 10 μL of 2X Laemmli buffer, and 20 μL of 1 mg/mL OprF1-biotin in 20 μL of 2X Laemmli buffer were used per well, respectively, asthe M13 phage detection and OprF1-biotin detection positive controls.

Conjugation of C-Terminal Modified Synthetic Peptide BREsto Quantum Dots. The Qdot 545 ITK Amino-PEG (Cat #:Q21591MP) and Qdot 525 ITK Amino-PEG (Cat #: Q21541MP)used in this study were obtained from ThermoFisher (ThermoFisherScientific, Waltham, MA) and have been fully characterized by thevendor. Detail physical and chemical characterization data includingcertificate of analysis and multiple publications describing the use andapplication of Qdots can be found at https://www.thermofisher.com/order/catalog/product/Q21591MP. Qdot Q21591MP presented thefollowing specification: full with at half-maximum ≤34 nm, relativequatum yield ≥47%, and emission maximum of 545 ± 4 nm. QdotQ21541MP presented the following specification: full width at half-maximum≤32 nm, relative quatum yield≥49%, and emissionmaximum525 ± 4 nm. Immediately before use, 3 mg of succinimidyl iodoacetate(SIA; ThermoFisher Scientific, Waltham, MA) was dissolved in 1 mL ofdimethylformamide (DMF), and 105 μL of this reagent was added to 60μL of 8 μM solution of quantum dots (QDs) in 50mM borate buffer pH8.3 (ThermoFisher Scientific, Waltham, MA). The reaction mixture wasrotated gently at 25 °C for 3 h in the dark. The reaction mixture wasdiluted with 1 mL of H2O and then transferred to an Amicon Ultra-4Centrifugal Filter 100 K (Merck Millipore Ltd., Carrigtwohill, Ireland).The reaction tube was washed twice with 1 mL of H2O to remove anyleftover QDs, and that was applied to the Amicon Ultra-4 CentrifugalFilter to concentrate the QDs by centrifugation at 5000 rpm for 15 minat 25 °C. The flow through was discarded, and 50 μL of SIA-QDconjugate was eluted into a clean microcentrifuge tube. The filter waswashed with 100 μL of H2O and combined with 50 μL of the SIA-QDconjugate. Synthetic peptide BREsmodified at the C-terminal with threeglycine and a cysteine were dissolved in 50 mM borate buffer pH 8.3 at 2mg/mL, and 300 μL was added to the 150 μL of SIA-QD conjugate. Thereaction mixture was rotated gently at 25 °C for 2 h in the dark, andpurified by using a gravity fed dextran desalting column MWCO 5 kDa(ThermoFisher Scientific, Waltham, MA) to remove low molecularweight molecules below 5 KDa including salts and unconjugatedpeptides. Product was eluted with 3−5 mL of 50 mM borate buffer pH8.3, and UV-active fractions from the dextran column elution werecollected and then concentrated using an Amicon Ultra-4 centrifugalfilter 100 K at 5000 rpm for 15min to remove any high molecular weightmolecules, including unconjugated SiA-Qdot aggregates that might haveformed during the process. Concentrated peptide BRE-QD conjugatewas eluted in a volume of 50 μL. The filter was washed with 150 μL ofH2O, and that was combined with the 50 μL of peptide BRE-QDconjugate to a final volume of 200 μL with a concentration of 2.4 μM;this highly UV-active fraction was used in the study.

Bacterial Labeling Method. Bacterial stocks for experimentationwere prepared by harvesting overnight grown bacterial cells bycentrifugation at 11000g for 15 min at 4 °C, washing once with 1XPBS pH 7.2, and resuspending in 1X PBS to a concentration of 1 × 109

cells/mL. Bacterial titers were determined by measuring optical densityat 600 nm and confirmed by colony counting on LB agar plates. Cellpellets produced by centrifuging 1 mL of the 1 × 109 cells/mL stockwere resuspended in 38 μL of 1X PBS, and 62 μL of 2.4 μMpeptide-QDwas added to a final concentration of 1.5 μM.Cells were incubated for 30min at 25 °C. Cell pellets were washed 3 times with 0.5 mL of PBS andresuspended in 500 μL of PBS for fluorescence assays and imaging.Dilutions ranging from 1 × 109 to 1 × 104 cells were prepared usingstandard bacteriological techniques, and 0.5 mL samples were used forfluorescence measurements and fluorescence microscopy.

Fluorometry. Emission spectra were obtained using a Cary Eclipsefluorimeter with excitation at 330 nm, scan rate of 120 nm/min, andPMT voltage of 1000 V. The spectra were corrected for background anddilution factor when appropriate.

Fluorescence Microscopy. Labeled cell samples were prepared asdescribed previously, and 10 μL of the sample was placed on amicroscope slide, covered with a coverslip, and visualized on a NikonEclipse Ti-E inverted microscope equipped with an X-Cite LED lamp,using a fluorescence filter set (a band-pass exciter 405 nm and a long-pass emission filter), and 40X (Plan Fluor, Nikon) and 100X oil-immersion objectives (DPlan 100X, Nikon). Images were captured witha Nikon DS-sCMOS camera. Scale bar = 10 μm.

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Limit of detection in fuel study. Samples containing 1 L of Jet Afuel were amended with 1 mL of 1X phosphate buffer solution (PBS)containing either A. venetianus ATCC 31012 or P. stutzeri at theappropriate test concentration. The inoculated jet fuel samples werethoroughly mixed for 1 min, and allowed to stand for 20min. To recoverthe cells, 1 mL of 1X PBS, named bacterial recovery solution (BRS), wasadded to the jet fuel samples, followed by shaking by hand and allowingthe sample to stand for 5 min, and then, 1 mL of the aqueous phase wascollected using a long serological pipet transferred to a microcentrifugetube and cells were pelleted by centrifuged for 5 min at 11000g; cellswere washed three times with 1 mL of 1X PBS. Bacterial pellets wereresuspended and labeled using a final concentration of 1.5 μM peptideBRE-QD, as explained in the bacterial labeling method. The LOD wasdefined as the lowest concentration level that could be determined to bestatistically different from QD-exposed cells from the results of multipletesters (n = 3). The actual cell level (colony-forming units, CFU)detected was determined by plating a portion of the sample after beingsubjected to the labeled procedure.Quantitative Real-Time PCR. Genomic DNA in fuel and water

samples was determined by quantitative real-time PCR (qPCR) using atwo-step amplification program with postamplification melt curveanalysis in a CFX 96 Touch real-time PCR system (BioRad, Hercules,CA) as previously described.13,31,56 Briefly, DNA levels were detectedand quantified using a bacterial universal 16S rrn gene primer set,57 incombination with a serially diluted (1 × 108 copies/μL to 1 × 103

copies/μL) synthetic oligonucleotide standard spanning the ampliconlength. The qPCR reaction contained 1 μL of forward and reverseprimer each at 200 nM final concentration, 12.5 μL of Biorad SYBRGreen SuperMix, 9.5 μL of water, and 1 μL of sample DNA for a finalvolume of 25 μL.Statistical Analyses. All measurements were performed in

triplicate, and their mean values ± SD (standard deviation) werecalculated using Microsoft Excel. Statistical analyses were performedusing Student’s t tests, and values were considered significantly differentwhen P < 0.05 (*).

■ ASSOCIATED CONTENT*S Supporting InformationThe Supporting Information is available free of charge on theACS Publications website at DOI: 10.1021/acs.energy-fuels.6b03350.

Heptameric amino acid sequences of OprF1 and Opr86-binding peptide biorecognition elements selected throughmultiple rounds of biopanning (PDF)

■ AUTHOR INFORMATIONCorresponding Author*E-mail: oscar.ruiz@us.af.mil.

ORCIDOksana M. Pavlyuk: 0000-0002-7131-8628Oscar N. Ruiz: 0000-0002-0263-6024NotesThe authors declare no competing financial interest.

■ ACKNOWLEDGMENTSResearch reported in this article was supported by funds from theUnited States Air Force Research Laboratory, Aerospace SystemsDirectorate to O.N.R. This material is based on researchsponsored by Air Force Research Laboratory under agreementnumber FA8650-10-2-2934. The views and conclusionscontained herein are those of the authors and should not beinterpreted as necessarily representing the official policies orendorsements, either expressed or implied, of Air Force ResearchLaboratory or the U.S. Government.

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Energy & Fuels Article

DOI: 10.1021/acs.energyfuels.6b03350Energy Fuels 2017, 31, 3747−3758

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