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Abstract
A new device with a 405 nm blue laser diode is developed for collecting samples in air and detecting their spectra variation. The multi-sample particles which are pure microorganisms can be distinguished from interferents in the air by photo-bleaching phenomenon. Six types of microorganisms and twelve types of interferents from the air, which exhibit laser-induced fluorescence, are used to evaluate the performance of the analysis approach, and their fluorescence emission spectra are presented. The results show that when microorganisms are illuminated by the laser, the fluorescence spectra will change significantly within several minutes, including both the wavelength of the main peak and fluorescence intensity. Our work provides a potential approach to distinguish microorganisms from other particles by the changes.
© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
1. Introduction
The detection of bioaerosols is a long-held focus of our research. Bioaerosols are suspensions of airborne particles that contain living organisms or particles released from living organisms [1]. However, the major focus of this research is the detection of harmful organisms in the air, such as bacteria and fungi. When the concentration of bacteria or fungi is high, human health may be harmed, and may even pose a threat to life. The traditional method for measuring the concentration of bacteria or fungi in the air is by culturing. However, this method takes 7–14 d to obtain a result. Hence, it does not meet the requirements of rapid detection.
Over the last two decades, since the discovery of the intrinsic laser-induced fluorescence (LIF) of microorganisms (bacteria and fungi), hybrid detection techniques, such as combined single-particle scattering and LIF techniques, have been rapidly developed [2]. However, researches have shown that many other substances, such as organic matter, plant remains, and pollen, can also be induced to fluoresce. Thus, it is difficult to accurately differentiate microorganisms (bacteria and fungi) from other particles in air only by fluorescence intensity. Hence, researchers have begun to investigate the fluorescence spectra of test samples. In 1995, S. C. Hill et al. developed an aerosol-fluorescence spectrum (AFS) analyzer with an argon-ion laser operating at 488 nm, which can measure the fluorescence spectra and elastic scattering of airborne particles [3], Y.L. Pan et al. designed an experimental device with double-wavelength excitation and a multichannel receiver; using this device, 16 varieties of atmospheric particles were tested [4]. Ø. Farsund et al. studied the differences between the fluorescence spectra excited by two different lasers, comparing 294 nm and 355 nm excitation wavelengths for reducing detection error rates [5]. Many biological agent warning sensors and single-particle fluorescence spectra analyzers resemble FLAPS [6–8]. Unfortunately, it is still difficult to differentiate microorganisms (bacteria and fungi) from aerosol accurately up to now, because the fluorescence spectra of some microorganisms and interferents are similar. Although it is hard to solve this challenge using only the LIF technique, their work is valuable and instructive.
In research of induced-fluorescence, photobleaching is an important phenomenon. Photobleaching is an accompanying process in the photodynamic reaction. At present, the process of photobleaching of most photosensitizers is not clear [9], and the bleaching products are also not clear, which hinders in-depth research and understanding of photobleaching [10]. However, we focus on using the photobleaching phenomenon to differentiate microorganisms from other particles in air, rather than studying the mechanism of photobleaching.
LIF and photobleaching of fluorescence are especially important in characterizing aerosol particles using Raman scattering. Raman spectroscopy (RS) has been used for over 40 years for the identification of materials including automobile exhausts, diesel exhaust [11], different bacteria [12], fungal spores [13], pollens [14] and soot [15]. Normally, Raman signals can be covered by fluorescence completely, and Raman spectra are measured after photobleaching within a reasonable time. It is also useful to reduce the number of particles for detection by Raman spectra. These common process modes all focus on eliminating or decreasing the influence of fluorescence. However, researchers have begun to recognize that the fluorescence in the Raman spectra is not just a hindrance but should also be useful. In 2016, D. C. Doughty and S. C. Hill developed an automated aerosol Raman spectrometer (ARS) for the semi-continuous sampling of atmospheric aerosol based on the Resource Effective Bioidentification System (REBS), and they found that the measured Raman spectrum was the sum of the Raman and fluorescence emission, therefore, the Raman spectrum could also provide information about the molecules that are fluorescent at the excitation wavelength [16]. In 2017, R. L. Craig et al. presented computer-controlled Raman micro spectroscopy (CC-Raman) for the rapid characterization of individual atmospheric aerosol particles. With a detailed post-analysis, useful information can be obtained from spectra that exhibit fluorescence and fluorescence microscopy or other techniques can potentially be used in correlation with Raman analysis to identify soot, biological, and other types of particles [17]. In addition, these two researches provide the foundation and reference for the development of automated RS, and will also boost the application of automated RS in atmospheric aerosol measurements.
Useful information could be obtained if we focus on both the fluorescence and Raman spectrum. In the detection of the Raman and fluorescence spectrum, it is found that the photobleaching of fluorescence is useful for the identification of substances. In this report, we combine the photobleaching phenomenon with other characteristics of fluorescence to differentiate microorganisms from other particles in air using new optical and detection systems.
2. Description of experimental arrangement
The principal components of the system are shown schematically in Fig. 1: an impactor (Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences) [18] for collecting target aerosol particles, a 405 nm blue laser diode (NICHA, Japan) for inducing the fluorescence, and a spectrograph (QE Pro, from Ocean Optics Asia) for detecting fluorescence. An instrument with a similar optical system had been developed by D. R. Huffman in 2016. Test samples were collected on a substrate, and a 405 nm laser diode or LED was used to induce fluorescence. Cameras were used to obtain the fluorescence and scattering light which pass through a grating to distinguish fluorescent and non-fluorescent particles [19]. Our spectrograph only detects the spectrum of fluorescence collected by the lens for distinguishing microorganisms from other particles. The details of the structure and the aim are different.
Fig. 1 Work functional diagram. The system consists of a radiation source, a glass slide, a light trap, two focusing lenses, a fluorescence filter, an impactor, an air pump, and a spectrograph.
In our experiments, the stable power of the 405-nm blue laser diode was 50 mW, and the irradiated area in the glass slide was 1 cm2. The wavelength range of our spectrograph was 200–1100 nm, and its optical resolution was 0.2 nm. The focal length of the lens was 23 mm, and its NA was 0.4.
The target aerosol to be detected was impacted on the center of the glass slide by the impactor, then the stepping motor rotated 90° and the laser irradiated the object obliquely, with the laser beam reflected by the glass slide and directed into the light trap. Two lenses were used for collecting the induced-fluorescence, and a long-pass fluorescence filter with a cut at 450 nm (JB450) was located in front of the focusing lens. We tested the performance of the fluorescence filter, and its measured transmission characteristics are illustrated in Fig. 2.
This test confirms that transmittance is >90% for wavelengths longer than 470 nm, and, when the wavelength was shorter than 440 nm, light was not transmitted by the fluorescence filter. Therefore, in the entire experiment, only wavelengths greater than 470 nm in the fluorescence spectrum were detected.
In order to reduce experimental errors in the analysis method, we also measured the laser power, the result of which is shown in Fig. 3.
According to Fig. 3, after the laser was switched on, its power decreased gradually over time, becoming stable after several minutes. From switch-on to stabilization, the laser power decreased by about 15%. Therefore, for all experiments, we waited for the laser power to stabilize before beginning measurements.
3. Experiment process and results
Our purpose is to differentiate bacteria and fungi from other particles in air. LIF technology, to differentiate fluorescent from non-fluorescent particles among aerosol, is facile. However, it is difficult to identify, from among the fluorescent particles, which of them are microorganisms because some particles in the air can also be induced to fluoresce. In the present work, we find a new method to solve this problem.
3.1. Experiment preparation and process
To evaluate the performance of the present method, we used a total of six types of bacteria or fungi (from American type culture collection (ATCC)) in our experiment, namely, Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, Bacillus subtilis spores, Candida albicans, and Aspergillus niger; and 12 types of interferents from which fluorescence can be induced and which are common in air, namely, green grass (Cynodon dactylon), green leaf (camphor tree), two kinds of pollen (Hippeastrum rutilum and Camellia), scraps of paper, dust, cigarette smoke, smoke from burning paper, scaling powder (RMA-218, KINGBO), nutrient agar medium, nutrient broth, and Model B800 fluorescent microspheres (produced by Thermo Scientific, USA). These 18 particle types are representative of the fluorescent objects in general environments. Of the 12 kinds of interferents: green grass (Cynodon dactylon), green leaf (camphor tree), and two kinds of the pollen are plant-based potential interferents. The fluorescent molecules in B800 particles are organic compounds, so these were used as a representation of possible organic compounds in the air. Scraps of paper, dust, cigarette smoke, and scaling powder are common in ordinary life.
As shown in Fig. 4, an aerosol generator capable of producing aerosols with different concentrations was adopted to generate the target aerosol. The target aerosol then formed a stable environment in the buffer bottle. Following this, the target aerosol particles, with sizes >0.5 um, were collected on the glass slide by the impactor. If the target aerosol was bacteria or fungi, a sampling apparatus would simultaneously collect the target aerosol for cultivating. If the target aerosol was another interferent, a particle counter would monitor its concentration.
Fig. 4 Experimental setup for performance evaluation of the monitor. The target aerosol is aerosolized by the aerosol generator, forming a uniform aerosol in the buffer bottle.
In order to suppress measurement interference from contaminants, we executed the following: The original stored frozen bacteria or fungi were placed into the culture dishes with nutrients and then were left to incubate under appropriate conditions, bacteria at 37 °C and fungi at 30 °C. Once the bacteria and fungi had revived and multiplied, they were placed in a centrifuge to separate them from the nutrients and were additionally washed with deionized water several times [20]. Green grass, green leaf, and other substances were chipped and their state in the air was simulated.
The complete experimental process is outlined as follows:
- (a) Stability of laser power: Before the test, we activated the laser and aligned it with the center of the glass slide, and waited several minutes for the laser power to stabilize. The area of the laser light spot was the focus of the collimating lens.
- (b) Collecting test substances: The object table was rotated 90° to collect the test samples by the impactor.
The bacteria or fungi were mixed with deionized water to form suspensions for generating aerosol.
For leaves and pollens, the experiment began within 30 min of picking the leaves. The pollen was collected fresh from flowers before used to generate aerosols.
For the other samples, an electric fan was used to provide a uniform distribution.
In our experiments, the concentration of bacteria or fungi in the buffer bottle was ~103 cfu/L or ~104 cfu/L, respectively, the other particle concentrations were about 5000 particle/L, and the common collection time was 1 min.
- (c) Obtaining the first spectrum: After switching back the object table, the test object on the glass slide was at the focal point of the lens, which was also the focal point of the correctly-aligned laser. At this moment, the first spectrum appeared on the computer, and was saved (Spectrum 1).
- (d) Obtaining the second spectrum: Irradiation continued for 5 min (the integral time of a spectrograph in our experiments was 100 ms, and the spectrum updated every 100 ms). After 5 min of irradiation, we saved the last spectrum (Spectrum 2).
- (e) Analyzing: The two spectra were compared and their differences analyzed.
3.2. Fluorescence spectrum of test objects
We obtained the spectra of 18 types of test substances in a series of experiments. In order to reflect the spectral differences more clearly, the spectra were normalized and smoothed. In addition, in order to make the spectra easier to understand, we added the position of the filter (JB450) in each figure. Figure 5 shows the spectra of six types of microorganisms; Fig. 6 shows the spectra of four types of interference of plant origin; and the spectra of the remaining samples are shown in Figs. 7–9.
Fig. 5 Fluorescence spectra of six types of microorganisms measured after zero and 5 min of laser exposure. The black line is representative of the filter (JB450) whose cut wavelength was 450 nm: (a) Staphylococcus aureus, (b) Escherichia coli, (c) Pseudomonas aeruginosa, (d) Bacillus subtilis, (e) Candida albicans, and (f) Aspergillus niger.
Fig. 6 Fluorescence spectra of potential interferent plant-based substances after zero and 5 min of laser exposure: (a) grass, (b) leaf, (c) pollen type 1 (Hippeastrum rutilum), and (d) pollen type 2 (Camellia).
Fig. 7 Fluorescence spectra of man-made potential interferent particles after zero and 5 min of laser exposure: (a) cigarette smoke, (b) smoke from burning paper, and (c) scaling powder.
Fig. 8 Fluorescence spectra of possible interferent particles that are common in air after zero and 5 min of laser exposure: (a) dust, (b) paper, and (c) B800 fluorescent microspheres.
In Fig. 5, we observe that not only does the main peak position shift significantly after 5 min of laser exposure, but the fluorescence intensity also decreased significantly. Moreover, some microorganisms had two or more peaks, and after laser irradiation, one peak disappeared. The LIF spectra of the potential interference plant-based substances are presented in Fig. 6.
From Fig. 6, we can observe that the main peak wavelengths of the spectra of all the plant-based substances were almost unchanged after 5 min of laser irradiation; the fluorescence intensities of the grass and leaf matter decreased significantly over this irradiation time, whereas the fluorescence intensity change for pollen was only slight.
The LIF spectra of man-made potential interferent particles, including smoke, are shown in Fig. 7.
According to Fig. 7, the main fluorescence wavelength peak of cigarette smoke shifts significantly after 5 min of laser irradiation, while the peaks of the other samples were almost unchanged; the fluorescence intensity of cigarette smoke and smoke from burning paper increased slightly in the same period, whereas the fluorescence intensity for scaling powder decreased dramatically.
Figure 8 shows the results of the measured florescence of some possible interferent particles that are common in air.
It is clear from observation of Fig. 8 that the main peak wavelengths of dust, paper, and B800 fluorescent microspheres were all almost unchanged after 5 min of laser irradiation, and the fluorescence intensities of all these samples decreased over the same irradiation time. The measured fluorescence spectra of nutrient agar and nutrient broth are shown in Fig. 9.
Figure 9 shows that the main peak positions for these substances were also unchanged after 5 min of laser irradiation, but the fluorescence intensity decreased.
3.3. Research of photobleaching rate
In this section, we give the photobleaching rate of microorganisms. Firstly, we measured the spectrum data of five groups within 5 min, respectively, at 0 s, 30 s, 90 s, 180 s, and 300 s. the results are shown in Fig. 10.
Fig. 10 Fluorescence spectra variation of six types of microorganisms in 5 min: (a) Staphylococcus aureus, (b) Escherichia coli, (c) Pseudomonas aeruginosa, (d) Bacillus subtilis, (e) Candida albicans, and (f) Aspergillus niger.
The fluorescence intensity was observed to decrease sharply at first, then more gradually. These results are described clearer in Fig. 11.
In our experiments, we found that the rate of spectral change increased with increasing laser power density. Furthermore, the spectral change also increased with a higher concentration of test microorganisms, but the changes were similar. When the laser power density is constant, different samples have different change rates. According to the results above, it seems there is no uniform rule between time of exposure and rate of spectral intensity decrease. In ongoing studies, further work must be completed on the change rule of the spectra.
3.4. Discussion for the changes of spectrum
In order to explain the above experimental results, we conducted a preliminary study for the fluorescent substances in the bacteria and fungi. The fluorescent substances in the bacteria and fungi that can emit after absorption at 405 nm wavelengths are principally Nicotinamide adenine dinucleotide (NADH), Riboflavin, and Dipicolinic acid (DPA). NADH and Riboflavin are normally present in bacteria and fungi, whereas DPA exists only in bacterial spores. NADH normally fluoresces at excitation wavelengths of about 340 nm (in the range 320–420 nm); Riboflavin normally fluoresces at excitation wavelengths of about 400 nm (in the range 320–420 nm) [21].
NADH, Riboflavin, and DPA were respectively mixed with deionized water to form a solution or suspension for generating a stable aerosol in the buffer bottle. The experiment equipment is shown in Fig. 4 and results of the measurements are shown in Fig. 12.
Fig. 12 Fluorescence emission spectra of the fluorescent molecules in bacteria and fungi: (a) NADH, (b) DPA, and (c) riboflavin.
These measurements show that the peak wavelength of the fluorescence spectra of NADH and DPA were fixed for the 5 min between measurements, but the fluorescence intensity slightly decreased with laser exposure time. However, for Riboflavin, the peak wavelength shifted, and the fluorescence intensity decreased dramatically.
As a result of these measurements, we considered that the changes of the fluorescence spectra of the microorganisms were partly due to the changes of the spectrum of Riboflavin. Although we have conducted some research on NADH, DPA, and Riboflavin, components of the microorganisms are complex, and we are unable to research them all. When the microorganism was irradiated by the laser, the amount of some components, like Riboflavin, in the cell decreased, but other components, like NADH and DPA, did not. Hence, the spectra of the microorganisms changes, as shown in Fig. 5.
When the laser wavelength is ~280 nm and ~360 nm, C. Pohlker et al. had researched the fluorescent biomolecules and potential interferences in bacteria and fungi and listed the excitation wavelength range of many fluorescence molecules [22]. But for 405 nm, further work must be conducted on the analysis of microorganism components and we would be grateful to discover other relevant work on this topic in the future.
3.5. Results and analysis
In order to obtain a basis for differentiating the 18 types of test objects, we produced a summary. After comparing the changes between the first spectrum and the second spectrum, measured after irradiation for 5 min by laser, for both cases, we considered two features: the main peak position shift percentage and the fluorescence intensity ratio (I5min/I0min). The summary data are presented in Fig. 13.
Fig. 13 Differentiation graph for all test objects using two measurement features, main peak position shift percentage and the fluorescence intensity ratio (I5min/I0min).
Figure 13 clarifies that the six kinds of microorganisms are different from the other 12 kinds of interferents under the same irradiation conditions. According to the two features, we could distinguish the microorganisms and others in air. In our experiment, their fluorescence emission intensities were reduced by more than 30% and the main peak positions shifted more than 2%. However, for other interferents that exhibited laser-induced fluorescence, the changes of their fluorescence spectra did not meet these two limiting conditions simultaneously. In addition, we also found that there are two fluorescence peaks when the object is Candida albicans, with one peak disappearing after laser irradiation, whereas, in the case of the other interferents that had two or more peaks, these spectral features were unchanged after irradiation.
4. Conclusions
This study focused on differentiating microorganisms from other particles in air by analyzing changes in their fluorescence spectra. A new system was developed for the experiments and 18 types of test substances were used to obtain results. The test substances included six types of microorganisms, namely, Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, Bacillus subtilis, Candida albicans, and Aspergillus niger; and 12 types of fluorescent particles, including green grass, green leaf, two types of pollen, scraps of paper, dust, cigarette smoke, smoke from burning paper, scaling powder, nutrient agar medium, nutrient broth, and standard fluorescent particles. The six types of microorganisms are typical examples: Staphylococcus aureus is a gram-positive coccus, Pseudomonas aeruginosa and Escherichia coli belong to gram-negative bacillus, and Candida albicans and Aspergillus niger are fungi.
We obtained the fluorescence emission spectra of the 18 types of substance, which are respectively original, and which are irradiated for 5 min by laser. Compared with the two measured spectra, we found that the six types of microorganisms are different from the other 12 types of fluorescent particles. After the microorganisms were illuminated by laser, the fluorescence spectrum changed significantly within several minutes, including changes to both the wavelength of the main peak and fluorescence intensity. In our experiments, the laser power density was 50 mW/cm2, the exposure time was 5 min, and the microorganism concentration in the buffer bottle was 103 cfu/L, the fluorescence intensity of the microorganisms reduced by more than 30% after laser exposure, and the wavelength of the main peak shifted more than 2%. For the other fluorescent particles, the changes in their LIF spectrum did not meet these two conditions simultaneously. In addition, we also found that there were two peaks in the spectrum of Candida albicans, but after laser irradiation, one of the peaks disappeared. For the other fluorescent particles with two or more peaks, the peak positions did not change after laser exposure. We also provided the photobleaching rate of microorganisms. The laser power density was higher and the rate of spectral change increased. When the laser power density was constant, different samples had different change rates. However, it seems that there is no uniform rule between time of exposure and rate of spectral intensity decrease. In order to explain this experimental result, we researched the fluorescence emission spectra of NADH, Riboflavin, and DPA, which can be induced by absorption of 405-nm laser light in bacteria and fungi. We considered that the changes of the fluorescence spectra of the microorganisms were partly due to the changes of the spectrum of Riboflavin.
Studies of other bacteria and fungi were outside the scope of this work. However, using our measurement method, it is feasible to carry out more experiments in the future with other bacteria and fungi. In addition, in this study, we did not examine the fluorescence spectra of single particles and did not research the Raman scattering, which is also important for the identification of substances. In future, we will continue to investigate in the field of bioparticle detection using laser-induced fluorescence and Raman scattering.
Funding
International Science & Technology Cooperation Program of Shanghai (1652071050); International Science & Technology Cooperation Program of China (Intergovernmental International Cooperation Program in Science and Technology Innovation, 2016YFE0110600);Youth Innovation Promotion Association CAS.
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