key: cord-1017390-jdquz3bq authors: Ma, Jinbiao; Du, Manman; Wang, Can; Xie, Xinwu; Wang, Hao; Zhang, Qian title: Advances in airborne microorganisms detection using biosensors: A critical review date: 2021-04-05 journal: Front Environ Sci Eng DOI: 10.1007/s11783-021-1420-8 sha: 498fcbd5be262cf4ec9d8099d8675bd19dbb6e39 doc_id: 1017390 cord_uid: jdquz3bq Humanity has been facing the threat of a variety of infectious diseases. Airborne microorganisms can cause airborne infectious diseases, which spread rapidly and extensively, causing huge losses to human society on a global scale. In recent years, the detection technology for airborne microorganisms has developed rapidly; it can be roughly divided into biochemical, immune, and molecular technologies. However, these technologies still have some shortcomings; they are time-consuming and have low sensitivity and poor stability. Most of them need to be used in the ideal environment of a laboratory, which limits their applications. A biosensor is a device that converts biological signals into detectable signals. As an interdisciplinary field, biosensors have successfully introduced a variety of technologies for bio-detection. Given their fast analysis speed, high sensitivity, good portability, strong specificity, and low cost, biosensors have been widely used in environmental monitoring, medical research, food and agricultural safety, military medicine and other fields. In recent years, the performance of biosensors has greatly improved, becoming a promising technology for airborne microorganism detection. This review introduces the detection principle of biosensors from the three aspects of component identification, energy conversion principle, and signal amplification. It also summarizes its research and application in airborne microorganism detection. The new progress and future development trend of the biosensor detection of airborne microorganisms are analyzed. [Image: see text] has not yet been effectively controlled globally. Indeed, frequent outbreaks of major airborne infectious diseases have been recently reported, which have had a significant impact on human life and health and on the global economy and society. According to the official report of the World Health Organization, the major infectious diseases in recent years are summarized, as shown in Table 1 . Every infectious disease is caused by specific microorganisms, including viruses, bacteria, fungi and parasites. Among them, microorganisms that spread through air are called airborne microorganisms (Després et al., 2012) . Airborne microorganisms can be transmitted through human exhalation (Doremalen et al., 2020) and show strong survivability in air. Airborne infectious diseases can be spread from person to person through airborne microorganisms (Hoehl et al., 2020; Yu et al., 2020; Jiang et al., 2021) . They spread rapidly and extensively (Setti et al., 2020) , which can easily cause social panic. (Zheng et al., 2018; Wang et al., 2019a) . Timely identification, monitoring, and investigation of airborne microorganism transmission in the human environment is particularly important to prevent the outbreak of airborne diseases in the population. At present, however, most of the test samples of airborne microorganisms come from clinical samples, which mainly include upper respiratory tract (nasopharyngeal swab and deep throat saliva), lower respiratory tract (alveolar lavage fluid and sputum), and body fluids (Cui and Zhou, 2020) . The collection of different types of samples can affect microorganism detection. Clinical samples often have high detection efficiency and accuracy, but they require professional operation and bring discomfort to the test subjects. Most technologies require on-site sampling and further tests in the laboratory, with complex operation process and long detection time (Wang et al., 2019a) . Correspondingly, the direct detection of air samples has received widespread attention in recent years, and air samples mainly include exhaled breath and aerosols (Razzini et al., 2020) . On-site air sample detection features a short detection time, flexibility, and convenience. However, it is easily affected by environmental factors such as wind speed, temperature, light intensity, and air humidity. In addition, the content of airborne microorganisms in the environment is low, with a wide variety of species and large number of impurities, which makes onsite detection difficult. The detection methods for airborne microorganisms can be roughly summarized as biochemical, immune, and molecular technologies. After years of development, some detection methods have become mature and new technologies are emerging constantly. However, most of the existing technologies have outstanding performance in aspects of detection time, specificity, and sensitivity, while some limitations exist in other aspects, which are difficult to meet the requirements of airborne microorganism detection. Several common detection methods are compared in Table 2 . In recent years, in view of the advantages and disadvantages of different detection technologies, diversified technology combinations have emerged, greatly improving the detection capabilities of airborne microorganisms (Zheng et al., 2018) . As an interdisciplinary field, biosensors have been extensively studied in recent years, Figure 1 summarizes technologies that have been successfully applied to biosensors or have the potential to be combined with biosensors. They have been widely used because of their short detection time, fast analysis speed, and flexible portability. As a routine laboratory microbial detection technology, biochemical technology is used in combination with biosensors for the preliminary treatment of samples (Peláez et al., 2020) . On the basis of the specific combination of antibody and antigen, immune technology introduces biosensors to construct an immunosensor, which has been extensively used in the detection of airborne microorganisms (Shen et al., 2009; Mavrikou et al., 2020) . Good results have been obtained for detecting SARS-CoV (Park et al., 2009) , Influenza virus A (Nidzworski et al., 2014) , AIV , SARS-CoV-2 (Seo et al., 2020) , and other airborne microorganisms. Molecular technology, as a new technology, can improve sensors, and it is mainly used for the identification of components and signal amplification of sensors (Xu et al., 2016; Freije et al., 2019) . Zhang et al. developed a nanosensor combined with RT-PCR amplification and achieved the rapid detection of dengue virus using a PNA probe binding on it (Zhang et al., 2010) . As an interdisciplinary field, biosensors integrate the advantages of many technologies and have bright prospects in the detection of airborne microorganisms. Biosensor is a special device that uses component identification as the biological sensing unit, converting biological signals into detectable signals using an appro-priate energy conversion principle. It also uses appropriate methods to achieve signal amplification with high selectivity to the target object. Its basic composition is shown in Fig. 2 . The detection of biosensors is realized by the specificity of component identification. According to the different component identification used, biosensors can be divided into two categories. The first type is the cell-based biosensor (Mavrikou et al., 2020) , which has certain requirements on the state and activity of the cell. It monitors and analyzes the changes in metabolites during cell respiration (Xu et al., 2016) . The second category is the biosensor based on the detection of microbial metabolites, including sensors based on aptamers , antibodies (Seo et al., 2020) , and nucleic acids (Liu et al., 2018c) . This type of biosensor has no special requirements for the survival state of microbial cells and is a commonly used for the component identification of biosensors. Gopinath et al. selected the 16 kDa heat shock protein of Mycobacterium tuberculosis (MTB) for component identification and coupled it to gold nanoparticles with a detection limit as low as 100 fM (Gopinath et al., 2016) . Aptamers are artificially synthesized short singlestranded DNA or RNA, which can develop high-affinity molecules to specifically recognize the desired target. Aptamers have many advantages compared with antibodies, such as short generation time, low manufacturing cost, high variability, good thermal stability and broad application (Zhang et al., 2019c) . Kwon et al. used aptamer biosensors to directly detect avian influenza virus in clinical samples of chicken serum, with a detection limit of 5.9 pM (Kwon et al., 2020) . The biosensor uses the principle of appropriate energy conversion to convert identifiable biological signals into detectable electrical, optical, acoustic, or thermal signals. In recent years, electrical and optical biosensors have developed rapidly. Electrical biosensors are the most widely used and the earliest developed biosensors in the field (Cesewski and Johnson, 2020) . This type of biosensor mainly uses electrical signals for detection, such as electrochemistry, field-effect transistor (FET), and piezoelectric sensors. The electrochemical biosensor uses the electrochemical signal generated by the biorecognition process on the electrode surface for detection. Depending on the signal type, electrochemical biosensors can be divided into three types of sensors: volt-ampere (Seo et al., 2020) , impedance (Xu et al., 2016) , and ampere (Bhattacharyya et al., 2016) . The FET biosensor uses the biological recognition process to cause changes in the electronic characteristics of semiconductor channels for detection. The Piezoelectric sensor uses the biometric process to detect surface charges when piezoelectric materials are pressed. Mavrikou et al. used a new type of electrochemical sensor to detect the S1 spike protein expressed on the surface of the virus SARS-CoV-2. The results are provided within 3 min, and the detection limit is 1 fg/mL (Mavrikou et al., 2020) . Seo et al. constructed a FET biosensor, detected the spike protein of SARS-CoV-2 at a concentration of 1 fg/mL, and successfully detected the culture medium (detection limit 16 PFU/ mL) and clinical specimens (detection limit 2.42 Â 10 2 copies/mL) of SARS-CoV-2 (Seo et al., 2020) . Zhang developed a new type of piezoelectric sensor combined with aptamer technology to detect MTB with a limit of 100 CFU/mL . The electrical biosensor is an important branch of biosensor, which fixes the bio-recognition element to the electrode surface, and converts the chemical or pressure signal generated by the combination of the target microorganism and the recognition element into a measurable electrical signal. It has been widely studied for its high sensitivity, fast response, high specificity, portability, and low cost (Cesewski and Johnson, 2020 ). The optical biosensor is a biosensor that converts the signal of the detected object into a detectable optical signal. Optical biosensors mainly utilize the properties of light, such as fluorescence , surface plasma resonance (SPR) (Peláez et al., 2020) and colorimetric (Briceno et al., 2019) sensors. The fluorescence sensor uses the unique photophysical properties of fluorescent nanomaterials for labeling and detection of microorganisms (Zheng et al., 2019) . The SPR biosensor uses the interaction of biomolecules to cause the instantaneous light signal change on the surface of the nano-layer metal film and then convert it into an electrical signal for detection. The colorimetric biosensor is based on the change in the number of target microorganisms in the sample, which can cause the color change of the detection solution to detect the target microorganisms (Wang et al., 2020a) . Wei et al. developed a fluorescent immunological biosensor that uses fluorescent dyes to modify DNA probes, which can be used to detect H5N1 antibodies in serum samples (Wei et al., 2013) . Peláez et al. used the SPR biosensor for the direct and label-free detection of the HspX recombinant antigen of MTB. Moreover, their process involved simple pretreatment of sputum specimens without any additional amplification steps, with a detection limit of 0.63 ng/mL (Peláez et al., 2020) . Briceno et al. used a colorimetric biosensor to complete detection within 20 min and can reach the sensitivity level of the culture method (Briceno et al., 2019) . The optical biosensor is an emerging research direction of sensing in recent years. Through biological or chemical luminescence sensing, real-time detection of the object can be realized without modifying the label of the target. The optical biosensor belongs to the category of traditional physical sensing, with sensitive response and strong antiinterference ability. In the detection of airborne microorganisms, the actual sample content is particularly low, so analysis and detection using conventional biological analysis methods are difficult to achieve. Certain methods are required to achieve signal amplification and improve the sensitivity of the sensor. Common signal amplification strategies include nanomaterial amplification technology (Xiao et al., 2020) , enzyme catalysis amplification technology (Xie et al., 2019a) , and nucleic acid-based amplification technology (Wu et al., 2019). The physical and chemical properties of nanomaterials are different from those of macroscopic substances, showing unique properties in optics, electricity, magnetism, biology, and other aspects. Nanomaterials have been extensively applied in the research of biosensors, greatly promoting the development of biosensors. Nano-functionalized materials are used as electroactive markers (Xiao et al., 2020) , enrichment materials (Briceno et al., 2019) , signal carriers (Gao et al., 2018) , and catalysts (Xie et al., 2019a) for signal amplification. In recent years, nanomaterials have been introduced into sensors to manufacture a large number of high-sensitivity sensing systems, which have excellent performance and long-term stability (Gao et al., 2018) . Shen et al. combined sensors with silicon nanowires to develop a real-time bioaerosol sensing system, which can observe the conductance changes of H3N2 viruses in a few seconds (Shen et al., 2011) . The hybrid structure of nanomaterials has attracted much attention due to its synergistic amplification effects. A platinum nanoparticle hybrid ZIF-8 composite biosensor can detect Salmonella at 11 CFU/mL (Wang et al., 2020a) . The gold nanoparticle hybrid fullerene nanoparticle/nitrogen-doped graphene nanosheet biosensor can detect MTB at 3 fM ). Enzymes are organic macromolecules with high selectivity and catalytic ability produced by living organisms. In biological analysis, enzymes are one of the most common signal markers. The catalytic effect of enzymes on substrates can transform the biochemical signals that are difficult to be detected into optical or electrical signals; meanwhile, the biological signals can be amplified to improve the detection sensitivity. Biological enzymes are subject to certain restrictions in application due to their high price and easy inactivation. In recent years, researchers have discovered that immobilizing enzymes on the surface of nanomaterials can not only increase the amount of enzyme immobilized, but also immobilize multiple enzymes at the same time, realizing the further amplification of the detection signal, and constructing nanocatalysts with mimic enzyme properties. Enzyme catalysis amplification technology has been used in the development of biosensors for its low cost, stable performance, and adjustable catalytic activity (Xie et al., 2019a ). Nucleic acid-based amplification technology is an amplification method that can transform a small number of nucleic acid molecules into a large number of nucleic acid amplification products. It is mostly used to detect specific accounting fragments of airborne microorganisms. Nucleic acid amplification technology can be divided into nonisothermal amplification technology (polymerase chain reaction [PCR] technology) and isothermal amplification technology (such as chain replacement amplification technology and rolling circle amplification technology) depending on reaction conditions. Zhang developed a biosensor based on Exonuclease III (Exo III)-assisted target recovery, which can recognize hybrid double strands and selectively digest DNA capture probes. This process improved the sensor's sensitivity, and it can detect 20 CFU/mL MTB ). Liu et al. improved the silicon photonic microcircle sensor using recombinase polymerase amplification technology, which increased the detection sensitivity of the sensor by three times (Liu et al., 2018c) . Biosensors have made considerable progress in the detection of airborne microorganisms. Tables 3, 4, and 5 summarize the applications of biosensors in the detection of airborne viruses, bacteria, and other microorganisms, respectively, and present the sensor types, sample types, detection concentration range, detection limit, response time and detection target for the detection of different microorganisms. Figure 3 summarizes the response time and detection limit of several common sensors for the detection of specific substances of airborne microorganisms. Thus, the response time of the sensor is mostly concentrated in the minute level, and the detection limit for specific substances can be as low as "zM" (10 -21 mol/L). Compared with other airborne microorganisms, the virus has a lower detection limit and a shorter response time. Electrochemical sensors have been extensively used, with detection limits spanning multiple orders of magnitude of dynamic range, and can quickly detect low-concentration microorganisms. In recent years, some new technologies have been used to optimize biosensors to detect airborne microorganisms, and the performance and efficiency of the biosensors have improved. For example, air sampling technology is used to solve of low content of microorganisms to be tested in environmental aerosol samples and improve the sensitivity of the biosensor. Purification and separation technology can improve the anti-infection ability of biosensors and solve the problems of excessive impurities in environmental aerosol samples. Microfluidic technology can Although clinical samples such as nasopharyngeal swabs can be used for detection, traditional sampling methods can make patients feel uncomfortable and cause sneezing to produce aerosols, which can cause potential health risks (Cui and Zhou, 2020) . At present, biosensors use air sampling systems to directly detect air samples. For infectious disease hotspots, the rapid detection of airborne microorganisms in air samples is necessary, and air sampling is often the first critical step (Shen et al., 2012) . Wen et al. developed an air sampling method for Gramnegative bacterial marker endotoxin, optimized the analysis method based on the limulus reagent test (Wen et al., 2017) , and detected 37.9-97.6 EU/m 3 endotoxin in the air of a university campus (Liu et al., 2018a) . Zheng et al. used an exhaled air condensing device to obtain 300 µL of air sample within 3 min, and combined it with isothermal amplification technology to successfully detect seven airborne microorganisms from exhaled breath (Zheng et al., 2018 The actual sample has impurity interference and the content of microorganisms in environmental aerosols is low. Directly collecting airborne microorganisms can be very challenging. Therefore, the samples for sensor detection must be preprocessed. Immunomagnetic separation has been extensively used in sample pretreatment. However, this method has shortcomings such as high requirements and low efficiency, that limit its application. Wang et al. used a magnetic grid separation column without any pre-enrichment of bacteria to complete the separation of 70% of target Salmonella cells in a 50 mL bacterial sample in 2.5 h, greatly improving the sensitivity of the sensor (Wang et al., 2020a) . Song et al. proposed an optimized collection and detection scheme for complex air samples, which can break the wall of airborne microorganisms without destroying the internal structure, thereby improving the detection efficiency . Briceno et al. added a magnetic field to the nanoparticles combined with MTB to achieve separation and enrichment, and the concentration rate of MTB could reach 47%, without using any expensive consumables and equipment (Briceno et al., 2019) . Existing sensors mostly use the drip method to measure samples, making the loading and processing of samples difficult to control. This method is susceptible to interference from external physical factors such as light, humidity, and temperature, resulting in inaccurate measurement and poor sensing stability. Microfluidic technology integrates sample preparation, reagent manipulation, biological reactions, and detection steps on a unique platform, which can simplify complex analysis schemes and reduce sample volume, detection time, and reagent costs (Nasseri et al., 2018) . Khan et al. integrated graphene and microfluidic devices to enhance the sensing performance, such as detection limit and sensitivity and continuous monitoring; the detection limit for thrombin reached 2.6 pM (Khan et al., 2020) . Xie et al. used a highthroughput microfluidic chip to construct an electrical impedance sensor, and successfully distinguished different forms of yeast, which can be used as a rapid analysis technique to airborne microorganisms (Xie et al., 2019b) . To improve the detection efficiency of biosensors and the portability of outdoor operations, multiple samples or multiple target microorganisms need to be detected at the same time to increase practicability and flexibility (Liu et al., 2018b) . Liu et al. combined four micro-ring sensors to realize real-time measurement and multiplexing of four samples, greatly improving the detection speed (Liu et al., 2018c) . Kumar et al. used peptide nucleic acids to induce color changes caused by aggregation of gold nanoparticles, which can be used to simultaneously detect multiple influenza viruses (Kumar et al., 2020) . The combination of biosensors and smart devices can make them flexible and portable; capable of real-time, continuous, and rapid detection; and has unique advantages such as miniaturization, high sensitivity, and absence of tags (Yang and Gao, 2019; Xing et al., 2020) . The introduction of smart devices has greatly improved microorganism detection and provided convenient data processing and transmission for demonstration purposes (Nasseri et al., 2018) . Mavrikou et al. combined a biosensor with a customized portable readout device operated by a smart phone/tablet computer for the portable detection of the new coronavirus spike protein within 3 min, with a detection limit of 1 fg/mL (Mavrikou et al., 2020) . Zheng et al. developed a new type of biosensor and used a smartphone imaging APP to monitor the color changes of AuNPs to determine the number of bacteria. The detection limit for Escherichia coli in chicken samples was 50 CFU/mL (Zheng et al., 2019) . The current recurrence of airborne infectious diseases is not optimistic, and the COVID-19 pandemic threatens to interfere with public health services. Reversing the recent progress in reducing the burden of airborne infectious diseases will lead to a reduction in the detection of infectious diseases and an increase in deaths. Therefore, rapid detection and point-of-care (POC) analysis of airborne microorganisms that cause these diseases are important. Among the various methods used to detect airborne microorganisms, biosensor technology is at the forefront of POC device development. In recent years, scientists have conducted extensive research on biosensor technology. Some biosensors have been gradually used to detect microorganisms in air, and good results have been achieved. However, some challenges in sensors need to be further resolved in the future: 1) The detection of air samples requires further research. Most of the biosensor samples used for the detection of microorganisms in air are tested under laboratory conditions, and the test samples are usually limited to ideal samples, such as recombinant proteins or cell culture fluids, which are often different from actual samples. 2) An intelligent integrated system of sensor air collection and detection should be developed. Such a system integrates air collection, sample pretreatment, specific detection, and other steps. It also minimizes errors caused by manual operation, improves detection efficiency, and realizes fast and portable detection. An integrated system is essential to determine whether the sensor can leave of the laboratory to be tested. 3) Reduce costs, improve stability, and realize commercial production. Given the current outbreak of global infectious diseases, to expand the detection range, costs should be reduced, standardized sensor preparation and functionalization should be carried out, and more sensor characterization methods, such as expressing sensor detection performance in advance through the working characteristic curve, should be developed. Thus, largescale commercial production can be realized. 4) Optimize the repeatability of the sensor. Given that the recognition and binding of biomolecules is often irreversible, most existing sensors are disposable products, and rebirth is difficult to achieve. The current rebirth effect is also uneven, and there is no unified standard that defines it. This is an important reason for limiting the large-scale application of sensors. 5) Further improve the specificity and sensitivity of the sensor. As a result of the low concentration of air microorganisms, detection is difficult, which affects the detection sensitivity of the sensor, and impurities are likely to cross-react and affect the detection specificity. New and more sensitive specific biological recognition elements must be developed. 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electrochemical immunosensor for detection of diphtheria toxoid A sensitive voltammetric biosensor for Escherichia coli detection using an electroactive substrate for beta-D-glucuronidase Acknowledgements This study was supported by the National Natural Science Foundation of China (Grant No. 51678402) and the Tianjin New Crown Epidemic Emergency Project (No. 20ZXGBSY00100).