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Minireview Potential of Laser-Induced Fluorescence-Light Detection And bs_bs_banner Minireview Potential of laser-induced fluorescence-light detection and ranging for future stand-off virus surveillance Oloche Owoicho,1,2 Charles Ochieng’ Olwal1,2 and contaminated surgical equipment or released amidst Osbourne Quaye1,2 other primary biological aerosol particles in labora- 1West African Centre for Cell Biology of Infectious tory-like close chamber. It has also been shown to Pathogens (WACCBIP), University of Ghana, Accra, distinguish between different picornaviruses. Cur- Ghana. rently, the potentials of the LIF-LiDAR technology for 2Department of Biochemistry, Cell and Molecular real-time stand-off surveillance of pathogenic viruses Biology, College of Basic and Applied Sciences, in indoor and outdoor environments have not been University of Ghana, Accra, Ghana. assessed. Considering the increasing applications of LIF-LiDAR for potential microbial pathogens detec- tion and classification, and the need for more robust Summary tools for viral surveillance at safe distance, we criti- cally evaluate the prospects and challenges of LIF- Viruses remain a significant public health concern LiDAR technology for real-time stand-off detection worldwide. Recently, humanity has faced deadly viral and classification of potentially pathogenic viruses infections, including Zika, Ebola and the current sev- in various environments. ere acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The threat is associated with the abil- ity of the viruses to mutate frequently and adapt to Introduction different hosts. Thus, there is the need for robust detection and classification of emerging virus strains Microbial pathogens such as bacteria, viruses, fungi and to ensure that humanity is prepared in terms of vac- parasites are a major public health concern. Of these, cine and drug developments. A point or stand-off viruses have proven to be a great threat in recent times. biosensor that can detect and classify viruses from Humanity has been faced with deadly viral infections indoor and outdoor environments would be suited including Zika virus, Ebolavirus and the ongoing severe for viral surveillance. Light detection and ranging acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (LiDAR) is a facile and versatile tool that has been pandemic. The viral threat is attributed to their ability to explored for stand-off detection in different environ- mutate frequently and adapt to different hosts. To out- ments including atmospheric, oceans and forest compete these viruses, there is the need for robust sensing. Notably, laser-induced fluorescence-light detection and surveillance of emerging strains. This will detection and ranging (LIF-LiDAR) has been used to ensure that humanity is prepared in terms of vaccine identify MS2 bacteriophage on artificially and drug development. A promising approach in this respect is a point or stand-off biosensor that can detect and classify viruses phylogenetically or based on their Received 16 May, 2020; revised 16 October, 2020; accepted 19 pathogenicity from indoor and outdoor environments. October, 2020. Stand-off detection and identification systems are For correspondence. E-mail [email protected]; Tel. (+233) 207 915923. defined by their ability to detect and classify chemical, Microbial Biotechnology (2020) 0(0), 1–10 biological and explosive (CBE) hazards without contact doi:10.1111/1751-7915.13698 with the hazardous material(s). The stand-off detection Funding informationOO and COO were supported by WACCBIP- ACE PhD fellowship (ACE02-WACCBIP: Awandare) and a DELTAS range may be considered short (also referred to as non- Africa grant (DEL-15-007: Awandare). The DELTAS Africa Initiative contact), medium or long, depending on the distance is an independent funding scheme of the African Academy of between the stand-off detector and the material being Sciences (AAS)’s Alliance for Accelerating Excellence in Science in Africa (AESA) and supported by the New Partnership for Africa’s targeted for detection. The stand-off detection range has Development Planning and Coordinating Agency (NEPAD Agency) been variably defined. Even though some studies have with funding from the Wellcome Trust (107755/Z/15/Z to Awandare) presented < 10 m and > 10 m as short and long stand- and the UK government. ª 2020 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. 2 O. Owoicho et al. off range, respectively (Bogue, 2018), this review adopts potentials for stand-off detection and characterization of the detection distances < 20 m, 20–100 m and > 100 m primary biological aerosol particles (PBAPs) (Buteau as short, medium and long stand-off detection range, et al., 2008; Li et al., 2019). LIF-LiDAR has been used respectively, in consonance with many other reports to identify MS2 bacteriophage on artificially contaminated (Sedlacek et al., 2002; Huestis et al., 2010; Babichenko surgical equipment (Babichenko et al., 2018). LIF-LiDAR et al., 2018; Fellner et al., 2020). Stand-off detection has also been used to identify MS2 bacteriophage methods are suitable for operations in high risk and amidst other PBAPs in laboratory-like close chamber harsh environments, as they could provide information and open field settings (Sivaprakasam et al., 2004; Bax- about CBE hazards in real-time from safe distances of ter et al., 2007; Jonsson et al., 2009; Farsund et al., several centimetres to up to a kilometre (Jonsson et al., 2010) and thus highlighting the potentials of the tech- 2009; Babichenko et al., 2018; Fellner et al., 2020). nique for viral detection indoors or outdoors. In addition, Based on these advantages, stand-off detection will be LIF-LiDAR was used to both detect and identify each an ideal approach for viruses, which can be highly con- virus from a pool of pure isolates of seven viruses of the tagious and dangerous. Picornavirus family (Gabbarini et al., 2019). However, Light detection and ranging (LiDAR) is a group of the potentials of the LIF-LiDAR technology have not techniques that are based on the principle that when a been assessed for real-time stand-off surveillance of pulsed laser (light amplification by stimulated emission of pathogenic viruses in the environment. In view of the radiation) impinges on particles, the particles absorb increasing applications of LIF-LiDAR for potential patho- and/or emit signals that can be characterized using a gens detection, and the need for more robust tools for suitable detector (Buteau et al., 2008). The emitted sig- non-contact viral surveillance at long range, this review nals could be a backward scattered or polarized light, or critically evaluates the prospect and challenges of LIF- fluorescence (Yang et al., 2016). LiDAR is a facile and LiDAR technology for stand-off surveillance of potentially versatile tool that has been applied in remote environ- harmful viruses in in-built or outdoor environments. mental monitoring, including atmospheric, oceans and In this review, we critically provide an overview of the forest sensing (Eitel et al., 2016; Almeida et al., 2019). types of LiDAR, LIF-LiDAR working principles, suitability LiDAR has also become a powerful air- or space-borne and prospects of LIF-LiDAR for virus surveillance, chal- altimetric tool (Flood, 2001; Forfinski-Sarkozi and Par- lenges of LIF-LiDAR approach in virus surveillance and rish, 2016). In addition, the LiDAR sensor is fast becom- a perspective on overcoming the potential challenges. ing a key component of autonomous vehicles, to provide information about the surroundings of the vehicles with Types of LiDAR high resolution (Royo and Ballesta-Garcia, 2019; Tang et al., 2020). Based on the nature of the scattered light, many types Based on the nature of the scattered light, four basic of LiDAR, including Rayleigh, Mie, Raman and reso- types of LiDAR, including Rayleigh, Mie, Raman and flu- nance fluorescence, have been described (Veerabuthi- orescence have been described (Veerabuthiran, 2003; ran, 2003; Zhang et al., 2011). Both Rayleigh and Mie Zhang et al., 2011). The laser-induced optical beha- scattering are elastic, meaning both incidence and scat- viours have been exploited for the detection and charac- tered light have the same wavelength, and no energy is terization of biogenic materials both in laboratory and lost as the incidence light impinges on the particles field conditions using LiDAR platforms. Raman scatter- (Veerabuthiran, 2003). For Rayleigh, the incident light ing, for example, has been applied spectroscopically to has a much longer wavelength than the size of the detect and identify pathogenic bacteria in clinical sam- impinged particle, while Mie scattering occurs when the ples (Ho et al., 2019) and determine antibiotics suscepti- particle has much larger size than the wavelength of the bility and transcriptomic profile that reflect antibiotics impinging light (Veerabuthiran, 2003). Unlike Rayleigh resistance in bacteria (Germond et al., 2018). A combi- and Mie scattering, Raman scattering is inelastic and nation of Rayleigh and Raman scattering effectively involves energy (or wavelength) shift, based on the characterized extracellular vesicles (EVs) and lipopro- molecular nature of the particles impinged by the light; teins, including differentiating tumour-derived EVs from the Raman energy shift is unique to different molecules
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