Adv. Opt. Techn. 2017; 6(2): 75–83 Research Article Open Access Frank Duschek*, Lea Fellner, Florian Gebert, Karin Grünewald, Anja Köhntopp, Marian Kraus, Peter Mahnke, Carsten Pargmann, Herbert Tomaso and Arne Walter Standoff detection and classification of bacteria by multispectral laser-induced fluorescence DOI 10.1515/aot-2016-0066 OCIS codes: 160.1435; 280.1415; 300.2530; 280.0280; Received December 2, 2016; accepted February 6, 2017; previously 000.3860. published online March 31, 2017 Abstract: Biological hazardous substances such as cer- tain fungi and bacteria represent a high risk for the broad 1 Introduction public if fallen into wrong hands. Incidents based on Hazardous bacteria represent a major threat to modern bio-agents are commonly considered to have unpredict- societies if released into the environment. Aerosols of bac- able and complex consequences for first responders and teria can occur naturally when infected animals or humans people. The impact of such an event can be minimized spread a pathogen, but they can also be released by acci- by an early and fast detection of hazards. The presented dents and as a terrorist attack. Once people are infected, approach is based on optical standoff detection apply- bacteria may easily spread aided by the fact that their detri- ing laser-induced fluorescence (LIF) on bacteria. The LIF mental effects can occur with a certain time delay. Therefore, bio-detector has been designed for outdoor operation fast and reliable detection and identification of bacteria is at standoff distances from 20 m up to more than 100 m. essential for the containment and the decontamination of The detector acquires LIF spectral data for two different affected areas and people. Commonly used methods for excitation wavelengths (280 and 355 nm) which can be bacterial identification are mass spectrometry, polymerase used to classify suspicious samples. A correlation analy- chain reaction, DNA sequencing and flow cytometry [1], all sis and spectral classification by a decision tree is used to of which are employed in the form of point sensors. These discriminate between the measured samples. In order to methods are highly sensitive and able to identify bacteria demonstrate the capabilities of the system, suspensions of very accurately. At the same time they require direct contact the low-risk and non-pathogenic bacteria Bacillus thuring- with a sample, can only be used to cover small areas, iensis, Bacillus atrophaeus, Bacillus subtilis, Brevibacillus and are not suitable for real-time detection or tracking of brevis, Micrococcus luteus, Oligella urethralis, Paenibacil- moving aerosol sources. Optical, i.e. laser-based methods lus polymyxa and Escherichia coli (K12) have been inves- on the other hand are capable of monitoring large areas in tigated with the system, resulting in a discrimination real time and from a safe distance. Here, additional chal- accuracy of about 90%. lenges lie in compensating the atmospheric interferences, Keywords: bacteria; biological agents; classification; i.e. incident sunlight, light scattering and absorption from laser-induced fluorescence (LIF); standoff detection. air, and airborne particles (pollen, dust, raindrops) and other weather-related phenomena. Furthermore, in inhab- *Corresponding author: Frank Duschek, German Aerospace Center, ited areas the used laser radiation must be eye-safe. Bio- Institute of Technical Physics, Langer Grund, Lampoldshausen, logical samples contain a large number of fluorophores. 74239 Hardthausen, Germany, e-mail: [email protected] Therefore, laser-induced fluorescence (LIF) yields high Lea Fellner, Florian Gebert, Karin Grünewald, Marian Kraus, Carsten Pargmann and Arne Walter: German Aerospace Center, Institute signal intensities at relatively low excitation energies [2, 3]. of Technical Physics, Langer Grund, Lampoldshausen, 74239 As fluorescence spectra usually show very few distinct fea- Hardthausen, Germany tures, the combination with sophisticated data analysis is Anja Köhntopp and Peter Mahnke: German Aerospace Center, necessary to increase specificity and sensitivity. The use of Institute of Technical Physics, 70569 Stuttgart, Germany several excitation wavelengths has been shown to strongly Herbert Tomaso: Friedrich-Loeffler-Institute, Institute of Bacterial enhance the capabilities for identification/classification Infections and Zoonoses, 07743 Jena, Germany [4]. Additionally, the fluorescence lifetime of bacteria has www.degruyter.com/aot been used to characterize a small set of them [5, 6]. © 2017 THOSS Media and De Gruyter ©2017, Frank Duschek et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. 76 F. Duschek et al.: Biohazard detection by LIF While spectroscopy on chemical solutions is rather In cooperation with LDI Innovations (Estonia), straightforward due to well-defined structures of chemical we presented a setup for dual-excitation wavelength agents, bacteria represent a more complex problem. They (280 nm, 355 nm) LIF detection and classification of dif- greatly differ in size and shape, and sometimes they form ferent bioorganic substances [20, 21]. The online classi- clusters, films or chains. Depending on the environmental fier used therein relies on spectral feature extraction and conditions bacteria can exist in different states, i.e. vegeta- selection and has been trained with a basic set of experi- tive cells, endospores or dead. As their chemical composi- mental spectra by bootstrap aggregation and a decision tion is very complex, a number of fluorophores contribute tree classification. The results showed the discrimination to the observed overall fluorescence. For Escherichia coli of a variety of bioorganic substances into four classes: 15 different fluorophores have been identified [7]. After plants, oils, chemicals and bacteria [3, 22]. excitation in the UV (280 nm) the observed fluorescence The next step is to investigate the ability to discrimi- is dominated by the amino acid tryptophan and shows nate different bacterial species with optical methods. smaller contribution from tyrosine, while at an excitation Here, we present the experimental results for a small set of wavelength of 355 nm, nicotinamide adenine dinucleotide eight different low-risk bacteria. Multispectral LIF spectra (NADH) and flavins are the main contributors. were recorded at a standoff distance of 22 m at excitation The discrimination of different bacteria by their intrin- wavelengths of 280 and 355 nm. Within this predeter- sic fluorescence has been demonstrated under laboratory mined group of bacteria, we demonstrate the discrimi- conditions [8, 9]. Furthermore, several approaches towards nation of samples containing different genera as well as a standoff detection system based on multiple-wavelength closely related bacteria by their LIF signature. LIF have been presented. Pan et al. [10, 11] developed an instrument that detects LIF from excitation wavelengths of 263 and 351 nm and scattering of single aerosol parti- 2 Experimental section cles. The instrument is capable of classifying airborne pollen and fungal particles. The US Naval Research Lab- 2.1 Experimental setup oratory presented a similar approach, in which the dual excitation wavelength fluorescence of single aerosol par- The standoff LIF detection system used in this study is operated on ticles is recorded in four different wavelength channels an outdoor optical test range at the German Aerospace Center, Lam- [12]. Under laboratory conditions, the discrimination of poldshausen. The laser and detection system is operated indoors, whereas the target is positioned outdoors. Experiments can be car- different biological and non-biological aerosol particles ried out with both generated aerosols and liquids in a cuvette. All by LIF techniques was successfully demonstrated [13]. data shown here were measured for suspensions at a distance of 22 m The Swedish Defence Research Agency (FOI) developed at both excitation wavelengths of 280 and 355 nm. a light detection and ranging (LIDAR) UV-LIF system for The experimental setup was designed as a generic system to be standoff aerosol detection, which has been field-tested used not only for LIF but also for Raman and laser-induced break- for the classification of different biological particles and down spectroscopy, which require higher spectral resolutions. As described in Section 4, a more dedicated LIF detection system with interferants [14]. The LIDAR technique has also been used compact detection optics and lower spectral resolution will be pre- by others, for example, research groups from Italy [15], sented in future work. India [16] and Canada [17, 18]. The Canadian SINBAHD system has gone through several field tests concerning 2.1.1 Optics: The schematic setup of the detection system is shown the recording of spectral signatures of different bacteria, in Figure 1. A frequency tripled Nd:YAG laser Spitlight 600-10 (InnoLas toxins and virus simulants under cross-wind conditions GmbH, Krailing, Germany) supplies pulses of 7 ns pulse length at at standoff distances up to the kilometer range. Recently, 355 nm with a repetition rate of 10 Hz. Each second pulse is frequency a scanning IR-LIDAR has been developed that monitors converted to 280 nm, resulting in an effective repetition rate of 5 Hz with pulse energies of about 10 mJ for each wavelength. For the the surroundings for aerosol clouds and triggers a staring generation of the