Detection of Aerosolized Biological Agents Using the Piezoelectric

Article pubs.acs.org/ac

Detection of Aerosolized Biological Agents Using the Piezoelectric Immunosensor David Kovár,̌ ‡ Zdeněk Farka,‡ and Petr Skládal* National Centre for Biomolecular Research and CEITEC MU, Masaryk University, Kotlárš ká 2, 611 37 Brno, Czech Republic S Supporting Information *

ABSTRACT: Airborne microorganisms are a major cause of respiratory diseases. Detection of pathogenic bacteria in the form of bioaerosols is required not only in peacetime but also in the threat of biological attacks. The label-free and direct detection of aerosolized biological agents is presented here. A desktop bioaerosol chamber for safe work with aerosolized microbial cells was constructed, and its functionality was tested. The model organisms (Escherichia coli) were disseminated using an aerosol generator in the chamber filled with either common laboratory indoor air or sterile air. The particles from the generated aerosol were collected using the cyclone SASS 2300, suspended in buffer and then analyzed using the piezoelectric immunosensor modified with specific capture antibodies. The frequency shifts indicated presence of the model biological agent with limit of detection of 1.45 × 104 CFU·L−1 of air. The total time from sample collection to detection was 16 min. The system was fully automated and controlled remotely through a local network.

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INTRODUCTION Airborne microorganisms (bacteria, viruses, fungi, etc.) are integral part of the natural and urban environments. Airborne bacteria originate from natural and anthropogenic sources, sometimes with the intent of targeted biological attacks or serious incidents.1,2 Bioterrorism is emerging as a real threat of the 21st century. The potential for abuse of biological warfare agents (BWAs) is too high as it was shown several times in modern history.3 The outdoor and indoor contamination of air with bacteria can relatively quickly lead to a large number of infected people. BWAs can be spread as contaminants of water supply and food or as bioaerosol contaminating indoor ventilation systems or disseminated outdoor by aircraft attacks.4 The detection of BWAs in the form of bioaerosol or pathogenic airborne bacteria is challenging due to the low concentration of target microbes and potential complexity of the sample matrix. The samples usually contain pollen grains, mold, fungi, dust, and ubiquitous microbial organisms.5 Also, a large number of industrial products emitted to the atmosphere by man may in principle interfere with the detection methods and make the detection of the target microorganisms highly complicated or even impossible. The composition of microorganisms in the atmosphere is still not well-defined. Together with these interferences, the low visibility, odorless, tasteless, and problematic sampling makes the analysis complicated. The delayed effect of biological agents in contrary to chemical agents, infectious character, and potentially larger number of casualties make it well suited for military or bioterrorist purposes.3 Also, the occurrence of pathogenic microorganisms in the air in places with a high population density contributes to the spread of epidemics and pandemics. In such cases, early © 2014 American Chemical Society

treatment must be initiated based on rapid detection and identification of the pathogen. The two key parts should be resolved during analysis of bioaerosols: collection of aerosol and detection of the bioagent. Extensive attention was focused on bioaerosol collecting systems: samplers.6 The function of the samplers is based on different physical principles and structural designs.7−10 The prime features characterizing samplers include operational flow rate of air, sampling time, volume of the collected samples, and cutoff size of the captured particles. Xu and Yao compared several portable widely used samplers on indoor and outdoor aerosols.11 The study summarized that different samplers resulted in different culturable bacterial bioaerosol diversity in various environments. Two different approaches toward detection of bioaerosols are used: either detection of general biological compounds present in air or direct specific detection of the target BWAs. The former choice utilizes optical methods, mainly fluorescence of the molecules present in biological systems12−14 (ATP, NADH, tryptophan, etc.). However, there are two disadvantages: (1) fluorescence-based instruments cannot distinguish between harmful or ubiquitous microorganisms, and (2) atmospheric pollutants may also fluoresce and consequently trigger false positive indications.15 Also, this concept is feasible only for living bacteria. The spores as a dormant form of certain bacterial species (e.g., Bacillus, Clostridium) exhibit very low levels of ATP and cannot be detected directly.16 Received: May 3, 2014 Accepted: August 4, 2014 Published: August 4, 2014 8680

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The second approach exploits the direct detection using culture-based methods, Raman spectroscopy, mass spectrometry,17,18 PCR techniques,19−21 particle ionization with potentiometric detection,22 alternatively FISH,7 surface-enhanced Raman spectroscopy (SERS),23 and differential mobility spectrometry (DMS).24 Personal bioaerosol sampler coupled with PCR was used for detection of vaccinia virus.25 However, complexities of analyzed samples containing interfering (bio)substances put PCR methods, which are by no means universally applicable to real-time monitoring of environmental samples, at a disadvantage,26 and additional methods are needed to avoid false conclusions.27 In the case of mass spectrometry (MS), extensive instrumentation limits widespread use for field detection. There is a need for reliable, quick-response, real-time, and on-site detection systems for use on a massive scale. Conventional microbiological methods are time-consuming and usually require collection of samples for subsequent laboratory analysis. This strongly depends on aerosol samplers used for collection of the microorganisms and on the desiccation stress characterized on the sampler.11 In contrary, biosensors have gained potential. Biosensors have many advantages in contrast with other developed methods for detection of microbes. The most important is the specificity given by the biological recognition factor which is followed by portability, miniaturization, and rapid response. The biosensors merge a convenient transducer with the efficient biological factor. As the transducer, optical,28−30 electrochemical,31,32 and piezoelectric33,34 sensors were successfully adopted. Either antibodies or nucleic acids (DNA probes, aptamers) can serve for the recognition. The viability or desiccation of microbes is not as relevant as in the case of the culture methods. The main question is the sensitivity of such biosensors. The United States Department of Homeland Security35 (DHS, USA) requires the sensitivity of field devices in the range from 102 to 105 organisms·L−1. Numerous protocols for detection of microorganisms employ the label-free assays. The main convenience is simplified protocol, quick response and no need of secondary labeled bioreagents. The most popular are impedance spectroscopy,36 surface plasmon resonance21,29,37,38 (SPR), and quartz crystal microbalance39,40 (QCM) sensors. In our previous study, we compared sensitivity of the SPR system Biacore with the QCM sensor on a Bacillus anthracis surrogate, concluding that both methods provided similar sensitivity.41 The use of QCM for label-free direct detection of bioaerosols should be feasible due to the preconcentration effect of the sampler. The QCM as a cheaper alternative to SPR is advantaged to widespread use for field detection and this possibility is evaluated in this work. The QCM is a relatively simple and sensitive device formed by thin quartz plate with gold electrodes on the opposite sides. The antibodies immobilized on its surface make QCM highly sensitive to the target antigen. The antigens interact with antibodies on the surface and increase the mass loaded on the surface which directly corresponds to the decreased frequency of the resonator. Nevertheless, the label free biosensors were not yet seriously considered for detection of bacteria from air. Several papers have been published about the detection of particles from air using QCM,42,43 but only two papers describe detection of bacteria.34,44 Here we present the detection of aerosolized bacteria using QCM, also comparing with culture based method and particle counter.

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EXPERIMENTAL SECTION

Chemicals and Reagents. Cysteamine and sulfosuccinimidyl-4-(N-maleimidomethyl)cyclohexane-1-carboxylate (Sulfo-SMCC) were purchased from Sigma (Germany). The chemicals for preparation of buffers (PBS, PBS-EDTA, and citrate), sulfuric acid, and potassium chromate for preparation of chromic acid were supplied from Penta (Czech Republic). Phosphate buffered saline (PBS, 50 mM sodium hydrogen phosphate/sodium dihydrogen phosphate; 150 mM sodium chloride; pH 7.4) was used for dissemination and QCM experiments. Citrate buffer (100 mM sodium citrate/citric acid; pH 4.0) was used for regeneration of the immunosensing surface. The buffers were filtered through a 0.22 μm PTFE membrane (Millipore, Germany) and autoclaved before use. Household bleach for disinfection of the aerosol chamber and contaminated parts of the apparatus was purchased from a local shop. The polyclonal antibody against Escherichia coli (43294906) was purchased from AbD Serotec (UK). BWA Model. As a model microorganism, E. coli strain K 12 was used. The strain (CCM 7929) was obtained as a lyophilized sample from Czech Collection of Microorganisms. The sample was revived in the Luria−Bertani low salt broth (Duchefa Biochemie, Netherlands) for 12 h, and the aliquots were stored frozen. E. coli was cultivated by the standard procedure. A volume of 100 μL of stock aliquot was inoculated in 100 mL of the low salt LB broth and aerobically cultivated overnight at 37 °C under gentle mixing. The bacteria were centrifuged at 4500 rcf for 10 min, and the pellet was washed thrice with PBS. The final PBS suspension was used for dilution of samples for aerosol experiments. Concentration of cells was determined by measuring absorbance at 600 nm using the McFarland calibration scale. The microbial suspensions for dissemination as the bioaerosol were diluted in PBS before use. Preparation of QCM Immunosensors. The antibody (Ab) was reduced by cysteamine.45 Briefly, the stock Ab was diluted in PBS-EDTA (100 mM PBS, 10 mM EDTA, pH 7.2) to a concentration of 2 mg·mL−1, and 1 μL of cysteamine (60 mg·mL−1, water solution) was added per each 10 μL of the Ab solution. The mixture was incubated for 90 min at 37 °C. The reduced antibodies (rIgG) were purified using the Microcon centrifugal unit YM 10,000 in accordance with the manufacturer’s instructions. The final concentration of rIgG was 3.5 mg·mL−1. Quartz crystals (10 MHz, AT-cut, gold electrodes) were purchased from International Crystal Manufacturing (USA). Prior to use, the gold electrodes were cleaned in chromic acid for 60 min and thoroughly washed with deionized water. The self-assembled monolayer was formed from aqueous cysteamine solution (20 mg·mL−1, 10 μL per electrode). The crystals were incubated in the dark for 2 h at 4 °C, washed with deionized water, and allowed to dry. Amine-containing surfaces were incubated with Sulfo-SMCC (3 mg·mL−1) for 1 h at room temperature, washed, and incubated directly with the reduced antibodies (rIgG, 100 μg·mL−1) for 18 h at 4 °C. After the last washing step, the crystals were either used or stored in dry state in refrigerator. The resonance frequency was measured after each modification step for verification of the immobilization steps (data not shown). Construction of the Air Chamber. The aerosol chamber was made of poly(methyl methacrylate). The dimensions of the box were 93 × 63 × 59 cm3 (total volume 0.346 m3). The removable front panel with attached handling gloves was locked 8681

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Figure 1. Scheme of desktop air chamber (not in scale): F, HEPA filters; P, air pumps; H, humidifier; S, syringe for filing the aerosol generator; FS, fluids switching unit. The sensor Comet was placed inside the chamber. Below the chamber, sensor systems, cyclone sampler linked to the immunosensor, network modules, and power supply adapters were placed. The blue lanes represent the airflow tracks, and the red lanes the liquid tracks. See the Supporting Information for the overall photo (Figure S3) and the diagram of flow-through system (Figure S4).

by screws. On the side panels, there were grommets for cables and valve hose brushings for safe manipulation and unplugging of the chamber with contaminated content from the rest of the measuring apparatus. Three fans with diameter of 12 cm and PWM speed control were placed inside the chamber to provide the turbulence and rapid mixing of the air inside. The axis of one fan was placed vertically to the bottom; the axes of the next two fans were placed angle-wise of 45° to the bottom. Aerosol generator was centered among the fans, it consisted of the ultrasonic piezoelectric element for terrariums (Reptile One, Australia) placed in beaker and covered with routing plastic plate streamlining the aerosol (Figure S1 in the Supporting Information). The samples were applied to this beaker from outside of the chamber using syringe and Teflon tube. The relative humidity, temperature and air pressure inside the chamber were monitored using the Comet 7511 sensor (Comet, Czech Republic). The particles size distribution, the outer temperature and outer relative humidity were measured using Met One 3400 (Hach). The counter measures particles in the range from 0.3 to 10 μm. The Met One was placed outside the chamber and the air from the interior was circulated through using the connected hose. The air humidifier SuperFog (LuckyReptile, Germany) was used for increasing the internal humidity where appropriate. Two air pumps (Hurricane, Italy) supplemented by HEPA filters (AirFilters, Czech Republic) were used for rapid exchange of sterile air inside the chamber. A Smart Air Sampler System, model SASS 2300 (Research

International) was used for collection of air samples. The SASS is a portable, wetted-wall cyclone sampler system developed for the collection of airborne materials. According to the user manual, it is particularly effective to capture aerosolized pathogenic bacteria and spores in the range of 0.5−10 μm. The cyclone collects the samples in liquid volume maintained constant during the sampling process. All apparatus used were controlled by software developed in-house (Delphi, Windows) for this purpose. The apparatus (Cyclone, Met One and all electronic accessories) were connected to the Serial Ethernet Server ESP904 (B&B Electronics) and controlled remotely via Ethernet link (see diagram of connections in Figure S2). Measuring Setup. Before the experiment and sampling the blank, normal air, the chamber was cleaned and the inner surfaces were sterilized using bleach. Prior to each experimental cycle, the chamber was ventilated out using two air pumps and then flushed by filtered air (HEPA filter) for 60 min. Then 10 mL samples (E. coli suspensions or PBS as blank) were loaded to the aerosol generator, and the humidity was increased to 80%. Three source concentrations of E. coli were used for dissemination: 107, 108, and 109 CFU·mL−1. To limit heating of the piezoelectric generator, five shorter cycles (60 s dissemination and 30 s break) were performed, hereafter referred to as full-cycle. Approximately 0.5 mL of BWA model suspension was disseminated as a bioaerosol fog per each fullcycle. Considering the total volume of the chamber (0.346 m3) and initial concentration of suspension, the initial concen8682

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Figure 2. Immunosensor responses for E. coli K 12 suspensions in PBS buffer. The association phase (10 min) and spontaneous dissociation of the formed immunocomplex due to flowing PBS are shown. Concentrations of bacteria are given in CFU·mL−1.

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trations of the spread BWA model were calculated as 1.45 × 104, 1.45 × 105, and 1.45 × 106 CFU·L−1 of air. The aerosol generation efficiency and the turbulence effect of fans were verified by culturing disseminated E. coli on agar plates placed in several parts inside the chamber (Figure S6). During the collection, the cyclone sampled the air from the chamber with a flow rate 360 L air/min. This means that the volume of the air chamber was passed approximately 4.8-times through the cyclone during the 5 min collection. The resulting preconcentration effect was theoretically 100-times, assuming that all fogged microorganisms were collected. Final volume of collected samples was 4.5 mL/5 min cycle. The sample holding loop (internal volume 400 μL) was implemented for dosing of collected samples to the immunosensor. The loop was always filled with the middle stream of liquid sample pumped from SASS 2300 using programmable electric valves. The forward and backward volumes were captured in vials. The scheme is shown in Figure S4; the system consists of two switching valves, sample loop, milliGAT pump (Global FIA, USA), in-house made flow-through cell with the QCM immunosensor, and vials for collection of the remaining sample volume. The QCM detection followed immediately after sampling. During the collection, the baseline of the immunosensor was stabilized in flowing PBS buffer. After filling the sample loop, the valves were switched and the sample was flown through the cell for 10 min followed by dissociation in PBS (10 min) and regeneration by citrate buffer (2 min). The pH change was sufficient for regeneration of the surface, and it allowed its reusability for 12−15 cycles. Then the activity of the sensor decreased rapidly. The sensor response to E. coli suspension throughout the whole experiment including regeneration phase is shown in Figure S9. The frequency changes were measured in real-time using the QCM analyzer (KEVA, Czech Republic). The flow rate for all solutions was 40 μL·min−1 except for the sample loop filling when the internal peristaltic pump of SASS 2300, which operates with constant flow rate of 4 mL·min−1.

RESULTS AND DISCUSSION Preparation of Immunosensors. Initially, eight individual immunosensors were modified with anti-E. coli antibody as described above. From this set, three immunosensors with similar final frequency shifts (sensors A−C) were chosen for performing measurements because of good reproducibility of individual immunosensors.46 The standard suspensions of bacteria were prepared by diluting the stock solution. The calibration curve for microbes in solution was measured using sensor A; the incubation period in flowing standard was 10 min. Typical frequency shifts for standard solutions (E. coli spiked in PBS) are shown in Figure 2; the regeneration phases are not shown. The frequency response was linear over a range from 105 to 107 CFU·mL−1, while the linear regression equation was Δf = −5.079log(CFU·mL−1) + 24.40 (R2 = 0.997). The limit of detection (LOD) was obtained as the concentration of E. coli in a sample for which the response reached 3 times the standard deviation (3σ) of the signal shifts of blank (3 repetitions). From the calibration graph presented in Figure S11, the LOD 7.5 × 104 CFU·mL−1 was determined for E. coli samples spiked in PBS. The matrix effect of environmental air samples was also studied. The outdoor air samples were collected using the cyclone sampler as described above. The air flow was constant and the same as in the case of collection from the chamber; only the time was increased for obtaining a sufficiently large volume of the working buffer. Afterward, E. coli was spiked into the working buffer (airPBS) in the same concentrations as before. The standard solutions were measured using sensor B (Figure S10), and the LOD was obtained similarly. The LOD 1.3 × 105 CFU·mL−1 was determined for spiked airPBS samples. The linear regression equation for graph shown in Figure S11 was Δf = −5.860log(CFU·mL−1) + 28.43 (R2 = 0.937). Based on these values, it can be assumed there is no significant matrix effect. The values suggest that the sensor provides similar results as published in the literature; Salmonella typhimurium was detected47 with LOD of 105 CFU·mL−1. The better LOD was achieved only through enhancing of the signal by nanoparticles.48 Jiang et al.49 compared different particles for amplifying and improving detection of E. coli O157:H7. Jiang’s 8683

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Figure 3. Comparison of data sets for particle size measurements: for blank (A) and disseminated concentration of E. coli 109 CFU·mL−1 (D). There are no significant differences between the blank and sample of dispersed E. coli in the measured aerosol. The data set (A) was started in a sterile and more or less particle-free air chamber. At point a, the humidity was increased to 80% and the internal environment was left to stabilize, point b. At point c, either the blank (A) or the sample (D) was dispersed. The increase in the concentration of particles is observed due to dispersing. The gaps in signal defined at points d indicate cyclone sampling.

group achieved the LOD of 106 CFU·mL−1 for label-free settings and lowered the LOD by 3 orders of magnitude using immunobeads. The preincubation of the samples or direct preconcentration using magnetic beads could further reduce the LOD value, but to the detriment of measuring time. In our case, the preconcentration step is provided via the cyclone air sampler, and the further preincubation or preconcentration seems not necessary for online real-time monitoring. The ability of antibodies to bind E. coli K 12 was imaged by atomic force microscope NanoWizard 3 BioScience (JPK Instruments, Germany) in the semicontact mode (Figure S7). The gold surface of QCM sensor was modified as described above. The surface was incubated with bacterial suspension in PBS (107 CFU·mL−1) for 1 h and consequently washed with sterile filtered PBS and shortly with sterile water. The nonincubated surface was used as a blank. The obtained images confirmed the expected function of the capture antibody. Testing Performance of the Aerosol Chamber. Initially, the dissemination efficiency was tested with the help of culturing of agar plates. The opened plates were placed inside the chamber in different positions and the suspension (107 CFU·mL−1) was disseminated in full-cycle to generate the bioaerosol. The plates were contacting the aerosol inside the chamber during the dissemination and cyclone collection. Afterward, the air containing bioaerosol was filtered out; the plates were removed, cultivated for 24 h at 37 °C and evaluated. The sterile PBS was used as blank and the plates were processed identically. The agar plate placed near the aerosol generator contained big microbial spots resulting from direct dropping of microbial suspension during the dissemination. The plates on the walls of the air chamber contained very small and well isolated point colonies, demonstrating sufficient quality of dissemination of the bacteria inside the air chamber (Figure S6). The amount of particles inside the air chamber was also monitored in real-time using the portable particle counter Met

One; this system provides distribution of particles in eight channels of increasing size intervals. The dissemination data sets of blank and concentration of E. coli of 109 CFU·mL−1 are shown in Figure 3. Comparison of other concentrations is shown in Figure S8. Each data set is characterized by increasing concentration of particles during the dissemination full-cycle and typical “gap” resulting from the cyclone collection; in the closed system, the much higher flow rate of air through the cyclone practically stopped the flow of air to the particle counter. Unfortunately, there was no apparent difference among the three disseminated concentration levels of bacteria or the blank and the counts of particles measured using Met One (with cyclone being switched off). When considering the size interval over 3 orders of magnitude, it was surprising that there were no differences for neither 1 nor 3 μm measuring channels. It seems that the response of the particle counter was mostly indicating different sizes of microdrops of the disseminated solutions. Detection of Bioaerosols. The bioaerosol samples were prepared by dissemination of several bacterial suspensions in the air chamber. For each concentration, two independent fullcycle disseminations were done and the “contaminated” air was collected by the cyclone sampler. The disseminated PBS without any microbes was used as a blank. The detection of samples was done in the flow-through immunosensor system connected online to the SASS cyclone. The responses (frequency shifts of sensor C) are shown in Figure 4. The data indicated that the minimal disseminated concentration was detectable and the concentration in the analyzed samples is below 1.5 × 104 CFU·L−1 of air. Assuming that 0.5 mL of the source suspensions dispersed throughout the volume of the air chamber, the theoretical concentrations of E. coli in the air and transferred in the buffer samples were calculated and are summarized in Table 1. Of course, this is the highest expected value, not considering partial condensation of the drops of the aerosol and sorption of microbial cells on the internal surfaces. However, the real 8684

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Table 1. Levels of E. coli in Air and in the Cyclone Samples during Dissemination of Bioaerosols disseminated concentration CFU·mL−1

level expected in air CFU·L−1

expected in PBS after capture CFU·mL−1

cultivation of samples CFU·mL−1

calculated from QCM response CFU·mL−1

107 108 109

1.45 × 104 1.45 × 105 1.45 × 106

1.11 × 106 1.11 × 107 1.11 × 108

90 2.5 × 103 8.1 × 103

6.69 × 104 1.63 × 105 2.89 × 106

detection of bacteria in aerosol using QCM. For this reason, the data measured here support the usefulness of combining the cyclone sampler with a piezoelectric immunosensor for reasonably fast detection of the target microbial cells in bioaerosols.

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CONCLUSION The aerosol chamber was constructed for safe and controlled dissemination of biological agents and applied for experiments with model bacterial aerosols of E. coli. The quartz crystal microbalance based piezoelectric immunosensor was used for label-free detection of bioaerosols after coupling with the air sampling cyclone SASS 2300. The whole setup was fully automated; the included liquid flow system was used for online delivery of the cyclone samples to the immunosensor detector, resulting in one detection cycle being completed in 16 min. The demonstrated limit of detection of E. coli in the collected aerosol samples was around 104 CFU·L−1 of air, based on the levels expected from the disseminated amounts of microbes. Total time needed for sample collection, detection, sensor regeneration, and ventilation of the chamber was 40 min. The reference culture based method proved that the disseminated concentration of E. coli in the air chamber was significantly reduced due to the surface adsorption, desiccation, or mechanical stress evoked by the cyclone. The important advantage of the developed system is the completely remote operation: the users are not in contact with the potentially dangerous bioagents during the experiments. Furthermore, the small dimensions, a desktop system, provide full portability of the experimental system; only power and Ethernet sources are required. The obtained data confirmed feasibility of the proposed combination of piezoelectric immunodetector with cyclone for promising detection of bioaerosols. The parallel detection of the most relevant pathogens using monoclonal antibodies immobilized on several sensors may in the future allow revealing a biological threat in reasonably short time intervals. The simple direct indication of the captured microbes is a single-step assay, and thus, the minimal complexity is favorable for high robustness and reliability of the whole system.

Figure 4. Frequency responses to samples collected by the SASS 2300 sampler. PBS buffer was disseminated as blank. The theoretically expected concentrations of E. coli in the generated bioaerosols are expressed in CFU·L−1 of air.

observed response of the immunosensor was approximately 2 orders of magnitude lower than one should expect from the theoretical calculation. The collected samples were also cultivated (Figure S12), and the real concentrations were extrapolated. The 100 μL of samples from the cyclone were smeared on the LB agar plates and cultivated for 24 h at 37 °C. The counted colonies were extrapolated using analytical software Icy (Institut Pasteur, France). This nondirect culture based detection method provided much lower real concentrations of E. coli in individual samples. The concentrations in the cultivated cyclone samples were calculated and are summarized also in Table 1. It should be mentioned that this is the lower limit of the microbes in the captured samples; the immunosensor should be responding also to the dead or partially damaged cells which are not appearing in the agar plates. In our experience with this kind of immunosensor, there are no significant differences between living, damaged, or dead bacteria. The total amount of lipopolysaccharides as main antigen does not vary in living suspension or suspension damaged by ultrasonication; hence, the signal is comparable for both suspensions with the same concentration of bacteria at the beginning. Accordingly, we use the CFU·mL−1 for expression of bacteria concentration; this is expected to be quite near values expressed as bacteria·mL−1. Previous information about coupling direct label-free immunosensors for detection of microbes in air is rather limited. Alava et al. used E. coli MRE 162 with a detection limit of 2.4 × 107 CFU·mL−1 in the collected air samples.44 However, details about preparation of air samples were missing in this paper. Usachev et al. used surface plasmon resonance for label-free real-time detection of the viral surrogate MS2 bacteriophage in bioaerosol; however, the LOD was not mentioned clearly.38 The aerosolized virus of influenza type A was detected using QCM coated with specific antibodies.34 Unfortunately, there are no other papers or studies concerning

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ASSOCIATED CONTENT

S Supporting Information *

Additional information as noted in the text. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Phone: +420 549 497 010. Author Contributions ‡

These authors contributed equally. The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.

Notes

The authors declare no competing financial interest. 8685

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ACKNOWLEDGMENTS The work has been supported by the Ministry of Defence of Czech Republic (Project Nos. OVVTUO2008001 and OSVTUO2006003) and by CEITEC - Central European Institute of Technology (CZ.1.05/1.1.00/02.0068) from European Regional Development Fund.

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dx.doi.org/10.1021/ac501623m | Anal. Chem. 2014, 86, 8680−8686