Optimizing Nanotechnology-Based Antimicrobial Platform for Food Safety Using Artificial Water Nanostructures (EWNS)

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Recently, a chemical-free antimicrobial platform based on nanotechnology using artificial water nanostructures (EWNS) has been developed. EWNS have a high surface charge and are rich in reactive oxygen species (ROS) that can interact with and inactivate a number of microorganisms, including foodborne pathogens. Here it is shown that their properties during synthesis can be fine-tuned and optimized to further enhance their antibacterial potential. The EWNS laboratory platform was designed to fine-tune the properties of EWNS by changing the synthesis parameters. The characterization of EWNS properties (charge, size, and ROS content) was performed using modern analytical methods. In addition, food microorganisms such as Escherichia coli, Salmonella enterica, Listeria innocua, Mycobacterium para fortitum, and Saccharomyces cerevisiae were inoculated onto the surface of organic grape tomatoes to evaluate their microbial inactivation potential. The results presented here demonstrate that the properties of EWNS can be fine-tuned during synthesis, resulting in an exponential increase in inactivation efficiency. In particular, the surface charge increased by a factor of four, and the ROS content increased. The microbial removal rate was microbially dependent and ranged from 1.0 to 3.8 log after 45 minutes of exposure to an aerosol dose of 40,000 #/cm3 EWNS.
Microbial contamination is the main cause of foodborne illness caused by the ingestion of pathogens or their toxins. Foodborne illness accounts for about 76 million illnesses, 325,000 hospitalizations, and 5,000 deaths each year in the United States alone1. In addition, the United States Department of Agriculture (USDA) estimates that increased consumption of fresh produce is responsible for 48 percent of all foodborne illnesses reported in the United States2. The cost of illness and death from foodborne pathogens in the United States is very high, estimated by the Centers for Disease Control and Prevention (CDC) at more than US$15.6 billion per year3.
Currently, chemical4, radiation5 and thermal6 antimicrobial interventions to ensure food safety are mainly implemented at limited critical control points (CCPs) in the production chain (usually after harvest and/or during packaging) rather than continuously implemented in such a way that fresh produce is subject to cross-contamination 7. Antimicrobial interventions are needed to better control foodborne illness and food spoilage and have the potential to be applied across the farm-to-table continuum. Less impact and cost.
A nanotechnology-based chemical-free antimicrobial platform has recently been developed to inactivate bacteria on surfaces and in the air using artificial water nanostructures (EWNS). For the synthesis of EVNS, two parallel processes were used: electrospray and water ionization (Fig. 1a). EWNS have previously been shown to have a unique set of physical and biological properties8,9,10. EWNS has an average of 10 electrons per structure and an average nanometer size of 25 nm (Fig. 1b,c)8,9,10. In addition, electron spin resonance (ESR) showed that EWNS contain a large amount of reactive oxygen species (ROS), mainly hydroxyl (OH•) and superoxide (O2-) radicals (Fig. 1c) 8 . EWNS remained in the air for a long time and could collide with microbes suspended in the air and present on surfaces, delivering their ROS payload and causing microbial inactivation (Fig. 1d). These earlier studies also showed that EWNS can interact with and inactivate various gram-negative and gram-positive bacteria of public health importance, including mycobacteria, on surfaces and in the air8,9. Transmission electron microscopy showed that the inactivation was caused by disruption of the cell membrane. In addition, acute inhalation studies have shown that high doses of EWNS do not cause lung damage or inflammation8.
(a) Electrospray occurs when a high voltage is applied between a capillary containing liquid and a counter electrode. (b) The application of high voltage results in two different phenomena: (i) electrospraying of water and (ii) generation of reactive oxygen species (ions) trapped in the EWNS. (c) The unique structure of EWNS. (d) EWNS are highly mobile due to their nanoscale nature and can interact with airborne pathogens.
The ability of the EWNS antimicrobial platform to inactivate foodborne microorganisms on the surface of fresh food has also recently been demonstrated. It has also been shown that the EWNS surface charge can be used in combination with an electric field for targeted delivery. More importantly, a promising initial result of approximately 1.4 log reduction in organic tomato activity against various food microorganisms such as E. coli and Listeria was observed within 90 minutes of exposure to EWNS at a concentration of approximately 50,000#/cm311. In addition, preliminary organoleptic evaluation tests showed no organoleptic effect compared to the control tomato. Although these initial inactivation results promise food safety even at very low EWNS doses of 50,000#/cc. see, it is clear that a higher inactivation potential would be more beneficial to further reduce the risk of infection and spoilage.
Here, we will focus our research on the development of an EWNS generation platform to fine tune the synthesis parameters and optimize the physicochemical properties of EWNS to enhance their antibacterial potential. In particular, optimization has focused on increasing their surface charge (to improve targeted delivery) and ROS content (to improve inactivation efficiency). Characterization of optimized physico-chemical properties (size, charge and ROS content) using modern analytical methods and using common food microorganisms such as E. coli, S. enterica, L. innocua, S. cerevisiae and M. parafortuitum.
EVNS was synthesized by simultaneous electrospraying and ionization of high purity water (18 MΩ cm–1). The electric atomizer 12 is typically used to atomize liquids and synthetic polymer and ceramic particles 13 and fibers 14 of controlled size.
As detailed in previous publications 8, 9, 10, 11, in a typical experiment, a high voltage is applied between a metal capillary and a grounded counter electrode. During this process, two different phenomena occur: 1) electrospray and 2) ionization of water. A strong electric field between the two electrodes causes negative charges to build up on the surface of the condensed water, resulting in the formation of Taylor cones. As a result, highly charged water droplets are formed, which continue to break up into smaller particles, according to the Rayleigh theory16. At the same time, a strong electric field causes some of the water molecules to split and strip off electrons (ionization), thereby generating a large amount of reactive oxygen species (ROS)17. Simultaneously generated ROS18 packets were encapsulated in EWNS (Fig. 1c).
On fig. 2a shows the EWNS generation system developed and used in the EWNS synthesis in this study. Purified water stored in a closed bottle was fed through a Teflon tube (2 mm inner diameter) to a 30G stainless steel needle (metal capillary). As shown in Figure 2b, the water flow is controlled by the air pressure inside the bottle. The needle is attached to a Teflon console that can be manually adjusted to a certain distance from the counter electrode. The counter electrode is a polished aluminum disk with a hole in the middle for sampling. Below the counter electrode is an aluminum sampling funnel, which is connected to the rest of the experimental setup via a sampling port (Fig. 2b). All sampler components are electrically grounded to avoid charge build-up that could degrade particle sampling.
(a) Engineered Water Nanostructure Generation System (EWNS). (b) Cross section of sampler and electrospray unit showing the most important parameters. (c) Experimental setup for bacteria inactivation.
The EWNS generation system described above is capable of changing key operating parameters to facilitate fine tuning of the EWNS properties. Adjust the applied voltage (V), the distance between the needle and the counter electrode (L), and the water flow (φ) through the capillary to fine-tune the EWNS characteristics. The symbols [V (kV), L (cm)] are used to denote different combinations. Adjust the water flow to get a stable Taylor cone of a certain set [V, L]. For the purposes of this study, the aperture of the counter electrode (D) was set at 0.5 inches (1.29 cm).
Due to the limited geometry and asymmetry, the electric field strength cannot be calculated from first principles. Instead, the QuickField™ software (Svendborg, Denmark)19 was used to calculate the electric field. The electric field is not uniform, so the value of the electric field at the tip of the capillary was used as a reference value for various configurations.
During the study, several combinations of voltage and distance between the needle and the counter electrode were evaluated in terms of Taylor cone formation, Taylor cone stability, EWNS production stability, and reproducibility. Various combinations are shown in Supplementary Table S1.
The output of the EWNS generation system was directly connected to a Scanning Mobility Particle Sizer (SMPS, model 3936, TSI, Shoreview, Minnesota) to measure particle number concentration and was used with a Faraday aerosol electrometer (TSI, model 3068B, Shoreview, USA). MN) to measure aerosol flows, as described in our previous publication9. Both the SMPS and the aerosol electrometer sampled at a flow rate of 0.5 L/min (total sample flow 1 L/min). Particle concentrations and aerosol fluxes were measured for 120 s. Repeat the measurement 30 times. The total aerosol charge is calculated from current measurements, and the average EWNS charge is estimated from the total number of EWNS particles sampled. The average cost of EWNS can be calculated using Equation (1):
where IEl is the measured current, NSMPS is the number concentration measured with the SMPS, and φEl is the flow rate to the electrometer.
Because relative humidity (RH) affects surface charge, the temperature and (RH) were kept constant at 21°C and 45%, respectively, during the experiment.
Atomic force microscopy (AFM), Asylum MFP-3D (Asylum Research, Santa Barbara, CA) and AC260T probe (Olympus, Tokyo, Japan) were used to measure the size and lifetime of the EWNS. The AFM scan rate is 1 Hz and the scan area is 5 µm×5 µm with 256 scan lines. All images were subjected to first order image alignment using Asylum software (mask with a range of 100 nm and a threshold of 100 pm).
Remove the sampling funnel and place the mica surface at a distance of 2.0 cm from the counter electrode for an average time of 120 s to avoid coalescence of particles and formation of irregular droplets on the mica surface. EWNS was applied directly to freshly cut mica surfaces (Ted Pella, Redding, CA). Immediately after sputtering, the mica surface was visualized using AFM. The surface contact angle of freshly cut unmodified mica is close to 0°, so EWNS propagates over the mica surface in a domed shape20. The diameter (a) and height (h) of the diffusing droplets were measured directly from the AFM topography and used to calculate the domed diffusion volume EWNS using our previously validated method8. Assuming that the onboard EVNS has the same volume, the equivalent diameter can be calculated from equation (2):
In accordance with our previously developed method, an electron spin resonance (ESR) spin trap was used to detect the presence of short-lived radical intermediates in EWNS. Aerosols were passed through a solution containing 235 mM DEPMPO (5-(diethoxyphosphoryl)-5-methyl-1-pyrroline-N-oxide) (Oxis International Inc., Portland, Oregon). All EPR measurements were performed using a Bruker EMX spectrometer (Bruker Instruments Inc. Billerica, MA, USA) and flat cell arrays. The Acquisit software (Bruker Instruments Inc. Billerica, MA, USA) was used to collect and analyze the data. The ROS characterization was performed only for a set of operating conditions [-6.5 kV, 4.0 cm]. EWNS concentrations were measured using SMPS after taking into account the loss of EWNS in the impactor.
Ozone levels were monitored using a 205 Dual Beam Ozone Monitor™ (2B Technologies, Boulder, Co)8,9,10.
For all EWNS properties, the measurement value is the mean of the measurements, and the measurement error is the standard deviation. A t-test was performed to compare the value of the optimized EWNS attribute with the corresponding value of the base EWNS.
Figure 2c shows a previously developed and characterized Electrostatic Precipitation Pass Through System (EPES) that can be used to target EWNS11 to surfaces. EPES uses an EWNS charge in combination with a strong electric field to “point” directly at the target’s surface. Details of the EPES system are presented in a recent publication by Pyrgiotakis et al.11. Thus, EPES consists of a 3D printed PVC chamber with tapered ends containing two parallel stainless steel (304 stainless steel, mirror polished) metal plates in the middle 15.24 cm apart. The boards were connected to an external high voltage source (Bertran 205B-10R, Spellman, Hauppauge, NY), the bottom board was always positive and the top board was always grounded (floating). The chamber walls are covered with aluminum foil, which is electrically grounded to prevent particle loss. The chamber has a sealed front loading door that allows test surfaces to be placed on plastic racks, lifting them off the bottom metal plate to avoid high voltage interference.
The deposition efficiency of EWNS in EPES was calculated according to a previously developed protocol detailed in Supplementary Figure S111.
As a control chamber, the second flow through the cylindrical chamber is connected in series with the EPES system using an intermediate HEPA filter to remove EWNS. As shown in fig. 2c, the EWNS aerosol was pumped through two chambers connected in series. The filter between the control room and EPES removes any remaining EWNS resulting in the same temperature (T), relative humidity (RH) and ozone levels.
Important foodborne microorganisms have been found to contaminate fresh produce such as Escherichia coli (ATCC #27325), a fecal indicator, Salmonella enterica (ATCC #53647), a foodborne pathogen, Listeria innocua (ATCC #33090), an alternative to the pathogenic Listeria monocytogenes. , Saccharomyces cerevisiae (ATCC #4098) as an alternative to spoilage yeast, and Mycobacterium parafortuitous (ATCC #19686) as a more resistant live bacteria were purchased from ATCC (Manassas, Virginia).
Randomly buy boxes of organic grape tomatoes from your local market and refrigerate at 4°C until use (up to 3 days). Select tomatoes to experiment with one size, about 1/2 inch in diameter.
The protocols for incubation, inoculation, exposure and colony counting have been detailed in our previous publications and explained in detail in Supplementary Data 11. EWNS performance was evaluated by exposing inoculated tomatoes to 40,000 #/cm3 for 45 minutes. Briefly, at time t = 0 min, three tomatoes were used to evaluate the surviving microorganisms. Three tomatoes were placed in EPES and exposed to EWNS at 40,000 #/cc (EWNS exposed tomatoes) and three others were placed in the control chamber (control tomatoes). None of the tomato groups was subjected to additional processing. EWNS-exposed tomatoes and controls were removed after 45 minutes to evaluate the effect of EWNS.
Each experiment was carried out in triplicate. Data analysis was performed according to the protocol described in Supplementary Data.
E. coli, Enterobacter, and L. innocua bacterial samples exposed to EWNS (45 min, EWNS aerosol concentration 40,000 #/cm3) and unexposed were pelleted to assess inactivation mechanisms. The precipitate was fixed for 2 hours at room temperature in 0.1 M sodium cacodylate solution (pH 7.4) with a fixative of 2.5% glutaraldehyde, 1.25% paraformaldehyde and 0.03% picric acid. After washing, they were fixed with 1% osmium tetroxide (OsO4)/1.5% potassium ferrocyanide (KFeCN6) for 2 h, washed 3 times with water and incubated in 1% uranyl acetate for 1 h, then washed twice with water. Subsequent dehydration 10 minutes each of 50%, 70%, 90%, 100% alcohol. The samples were then placed in propylene oxide for 1 hour and impregnated with a 1:1 mixture of propylene oxide and TAAP Epon (Marivac Canada Inc. St. Laurent, CA). The samples were embedded in TAAB Epon and polymerized at 60°C for 48 hours. The cured granular resin was cut and visualized by TEM using a JEOL 1200EX (JEOL, Tokyo, Japan), a conventional transmission electron microscope equipped with an AMT 2k CCD camera (Advanced Microscopy Techniques, Corp., Woburn, MA, USA).
All experiments were carried out in triplicate. For each time point, bacterial washes were plated in triplicate, resulting in a total of nine data points per point, the average of which was used as the bacterial concentration for that particular organism. The standard deviation was used as the measurement error. All points count.
The logarithm of the decrease in the concentration of bacteria compared to t = 0 min was calculated using the following formula:
where C0 is the concentration of bacteria in the control sample at time 0 (i.e. after the surface has dried but before being placed in the chamber) and Cn is the concentration of bacteria on the surface after n minutes of exposure.
To account for the natural degradation of bacteria during the 45 minute exposure period, Log-Reduction was also calculated compared to control at 45 minutes as follows:
Where Cn is the concentration of bacteria in the control sample at time n and Cn-Control is the concentration of control bacteria at time n. Data are presented as a log reduction compared to control (no EWNS exposure).
During the study, several combinations of voltage and distance between the needle and the counter electrode were evaluated in terms of Taylor cone formation, Taylor cone stability, EWNS production stability, and reproducibility. Various combinations are shown in Supplementary Table S1. Two cases were selected for a complete study showing stable and reproducible properties (Taylor cone, EWNS production, and stability over time). On fig. 3 shows the results on the charge, size and content of ROS for two cases. The results are also summarized in Table 1. For reference, Figure 3 and Table 1 include the properties of the previously synthesized non-optimized EWNS8, 9, 10, 11 (baseline-EWNS). Statistical significance calculations using a two-tailed t-test are republished in Supplementary Table S2. In addition, additional data include studies on the effect of the counter electrode sampling hole diameter (D) and the distance between the ground electrode and the tip of the needle (L) (Supplementary Figures S2 and S3).
(a–c) AFM size distribution. (d – f) Surface charge characteristic. (g) Characterization of ROS and ESR.
It is also important to note that for all of the above conditions, the measured ionization currents were in the range of 2-6 µA, and the voltages were in the range of -3.8 to -6.5 kV, resulting in a power consumption for this single-terminal EWNS of less than 50 mW. . generation module. Although EWNS was synthesized under high pressure, ozone levels were very low, never exceeding 60 ppb.
Supplementary Figure S4 shows the simulated electric fields for the [-6.5 kV, 4.0 cm] and [-3.8 kV, 0.5 cm] scenarios, respectively. The fields according to the scenarios [-6.5 kV, 4.0 cm] and [-3.8 kV, 0.5 cm] are calculated as 2 × 105 V/m and 4.7 × 105 V/m, respectively. This is to be expected, since the ratio of voltage to distance is much higher in the second case.
On fig. 3a,b shows the EWNS diameter measured with the AFM8. The average EWNS diameters for the [-6.5 kV, 4.0 cm] and [-3.8 kV, 0.5 cm] scenarios were calculated as 27 nm and 19 nm, respectively. The geometric standard deviations of the distributions for the cases [-6.5 kV, 4.0 cm] and [-3.8 kV, 0.5 cm] are 1.41 and 1.45, respectively, indicating a narrow size distribution. Both the mean size and geometric standard deviation are very close to baseline-EWNS, being 25 nm and 1.41, respectively. On fig. 3c shows the size distribution of the baseline EWNS measured using the same method under the same conditions.
On fig. 3d,e shows the results of charge characterization. Data are average measurements of 30 simultaneous measurements of concentration (#/cm3) and current (I). The analysis shows that the average charge on the EWNS is 22 ± 6 e- and 44 ± 6 e- for [-6.5 kV, 4.0 cm] and [-3.8 kV, 0.5 cm], respectively. Compared to Baseline-EWNS (10 ± 2 e-), their surface charge is significantly higher, twice that of the [-6.5 kV, 4.0 cm] scenario and four times that of the [-3 .8 kV, 0.5 cm]. 3f shows basic EWNS payment data.
From the EWNS number concentration maps (Supplementary Figures S5 and S6), it can be seen that the [-6.5 kV, 4.0 cm] scene has a significantly higher number of particles than the [-3.8 kV, 0.5 cm] scene. It should also be noted that EWNS number concentrations were monitored for up to 4 hours (Supplementary Figures S5 and S6), where the EWNS generation stability showed the same levels of particle number concentrations in both cases.
Figure 3g shows the EPR spectrum after control (background) subtraction for optimized EWNS at [-6.5 kV, 4.0 cm]. The ROS spectrum is also compared to the EWNS baseline in a previously published paper. The calculated number of EWNS reacting with the spin trap is 7.5 × 104 EWNS/s, which is similar to the previously published Baseline-EWNS8. The EPR spectra clearly indicated the presence of two types of ROS, where O2- predominated, while OH• was present in a smaller amount. In addition, a direct comparison of the peak intensities showed that the optimized EWNS had a significantly higher ROS content compared to the baseline EWNS.
On fig. 4 shows the deposition efficiency of EWNS in EPES. The data are also summarized in Table I and compared with the original EWNS data. For both EUNS cases, deposition was close to 100% even at a low voltage of 3.0 kV. Typically, 3.0 kV is sufficient to achieve 100% deposition regardless of surface charge change. Under the same conditions, the deposition efficiency of the Baseline-EWNS was only 56% due to the lower charge (average 10 electrons per EWNS).
Figure 5 and Table 2 summarize the degree of inactivation of microorganisms inoculated on the surface of tomatoes after exposure to approximately 40,000 #/cm3 EWNS for 45 minutes under the optimal scenario [-6.5 kV, 4.0 cm]. Inoculated E. coli and L. innocua showed a significant reduction of 3.8 log after 45 minutes of exposure. Under the same conditions, S. enterica showed a lower log reduction of 2.2 logs, while S. cerevisiae and M. parafortuitum showed a 1.0 log reduction.
Electron micrographs (Figure 6) depicting the physical changes induced by EWNS in E. coli, Salmonella enterica, and L. innocua cells leading to inactivation. Control bacteria showed intact cell membranes, while exposed bacteria had damaged outer membranes.
Electron microscopic imaging of control and exposed bacteria revealed membrane damage.
The data on the physicochemical properties of the optimized EWNS collectively show that the EWNS properties (surface charge and ROS content) were significantly improved compared to the previously published EWNS baseline data8,9,10,11. On the other hand, their size remained in the nanometer range, which is very similar to previously published results, allowing them to stay in the air for a long period of time. The observed polydispersity can be explained by changes in the surface charge, which determine the magnitude of the Rayleigh effect, randomness, and potential merging of EWNS. However, as detailed by Nielsen et al.22, high surface charge reduces evaporation by effectively increasing the surface energy/tension of the water drop. This theory was experimentally confirmed for microdroplets22 and EWNS in our previous publication8. The loss of overtime can also affect size and contribute to the observed size distribution.
In addition, the charge per structure is about 22–44 e-, depending on the circumstances, which is significantly higher compared to the basic EWNS, which has an average charge of 10 ± 2 electrons per structure. However, it should be noted that this is the average charge of EWNS. Seto et al. It has been shown that the charge is not uniform and follows a log-normal distribution21. Compared to our previous work, doubling the surface charge doubles the deposition efficiency in the EPES system to almost 100%11.


Post time: Nov-18-2022