1. School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China 2. Tianjin Key Laboratory of Indoor Air Environmental Quality Control, Tianjin 300072, China 3. Institute of Medical Support Technology, Academy of Military Science, Tianjin 300161, China 4. National Bio-Protection Engineering Center, Tianjin 300161, China 5. School of Electronic Information and Automation, Tianjin University of Science and Technology, Tianjin 300222, China 6. School of Mechanical Engineering and Safety Engineering, Institute of Particle Technology, University of Wuppertal, Wuppertal D-42119, Germany
• Airborne microorganism detection methods are summarized.
• Biosensors play an important role in detecting airborne microorganisms.
• The principle of biosensor detection of airborne microorganisms is introduced.
• The application and progress of biosensor in recent years is summarized.
• The future perspectives of biosensor are identified.
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.
8069 confirmed cases and 774 deaths (as at July 2003)
H1N1 Flu
Influenza virus A
Birds and mammals
2009.04–2010.08
68474274 confirmed cases and 18449 deaths (as at August 2009)
MERS
MERS-CoV
Camel
2012.09–2018.09
2562 confirmed cases and 881 deaths (as at September 2020)
H7N9 avian influenza
AIV
Poultry
2013.03–2017.09
1564 confirmed cases and 609 deaths (as at October 2017)
COVID-19
SARS-CoV-2
Bat*
2019.12–
More than 107 million confirmed cases and 2.3 million deaths (as at February 2021)
Tab.1
Detection method
Advantage
Disadvantage
Reference
Culture
1. Relatively simple operation 2. Low cost, and less equipment investment 3. Used for strain typing and drug resistance detection
1. Large workload, and long detection time 2. Low sensitivity 3. Difficult to cultivate some microorganisms or require high biological safety
Hudu et al., 2016; Gupta and Kakkar, 2018
Medical imaging
1. Short detection time 2. fast analysis speed
1. Need professional equipment 2. Low specificity 3. Invasive 4. Not suitable for early-stage patients
Brenner and Hall, 2007; Seibel et al., 2020
Immune technology
1. Medium sensitivity, capable of determining small or limited amounts of enzymes in samples 2. Medium specificity, not easily affected by impurities 3. Medium detection time, suitable for large number of samples
1. Prone to “false positives” affecting the results 2. Many measurement steps and complicated operation 3. High measurement cost
Phunpae et al., 2014; Fronczek and Yoon, 2015; Mekonnen et al., 2020
Polymerase chain reaction
1. High sensitivity 2. High specificity, low sample purity requirements 3. Used for strain typing and drug resistance detection 4. Medium detection time
1. High measurement cost 2. Complex cyclic process, high technical requirements, and professional equipment 3. Unable to distinguish between living and dead microorganisms
Weile and knabbe, 2009; Paolucci et al., 2010; Eddabra and Ait Benhassou, 2018
Gene Sequencing
1. Good stability, and specificity 2. High detection accuracy
1. Large workload, and long detection time 2. High measurement cost
Schlaberg et al., 2017
Biosensor
1. High sensitivity, and high specificity 2. Short detection time, and fast analysis speed 3. Flexible and portable, suitable for on-site testing 4. Low cost
Multichannel series piezoelectric quartz crystal (MSPQC) sensor
Culture /sputum
1 × 103 – 1 × 107CFU/mL
102 CFU/mL
70 min
H37Rv
Zhang et al., 2017
Silicon photonic microring sensor
Sputum
5 fg/uL– 500 pg/uL
3.2 copies
1 h
DNA
Liu et al., 2018c
MSPQC sensor
Culture /sputum
1 × 102 – 1 × 108CFU/mL
20 CFU/mL
3 h
H37Ra
Zhang et al., 2019a
Electrochemical Sensor
Culture
102 – 107 CFU/mL
102 CFU/mL
2 h
H37Rv
Zhang et al., 2019b
Electrochemical sensor
Synthesis
1 fg/mL – 1 ng/mL
0.33 fg/mL
–
Protein
Chen et al., 2019
SPR biosensor
Sputum
2 – 125 ng/mL
0.63 ng/mL
35 – 40 min
Protein
Peláez et al., 2020
Tab.4
Bio-substance
Sensor type
Sample
Range
Detection limit
Response time
Detection target
Reference
Aspergillus flavus
Electrochemical DNA biosensor
Aflatoxin B1 in pistachio nuts
1 nM – 10 μM
0.55 nM
4 h
DNA
Sedighi-Khavidak et al., 2017
Aspergillus niger
Cantilever sensor
Fungal strain A. niger
–
103 CFU/mL
4 h
Fungal spores
Nugaeva et al., 2007
Mycoplasma
Cantilever Sensors
Cell culture
103 – 107 CFU/mL
103 CFU/mL
Less than 1h
Mycoplasma
Xu et al., 2010
Electrochemical gene sensor
Synthesis
0.1 pM – 20 nM
0.03 pM
2 h
DNA
Liu et al., 2016
Fluorescence biosensor
Sheep serum
102 – 106 copies/μL.
1.042 copies/mL
Less than 15 min
Mycoplasma ovipneumoniae
Chen et al., 2017
Lateral flow biosensor
Oropharyngeal swab specimens
60 fg/uL – 60 ng/uL
600 fg/uL
1 h
DNA
Wang et al., 2019b
Lateral flow biosensor
Oropharyngeal Swab specimens
5 fg/uL – 5 ng/uL
50 fg/uL
1 h
DNA
Wang et al., 2019c
Fluorescence biosensor
Human saliva
5 – 300 nM
3.96 nm
10 min
DNA
Li et al., 2019
Rickettsia
Optical biosensor
Blood plasma/Liver biopsy samples
5 × 101 – 5 × 104 copies/reaction
5 × 101 copies/reaction
20 min
DNA
Koo et al., 2018
Chlamydia
Optical DNA biosensor
Human urine
0.25 – 20 nM
0.25 nM
–
DNA
Parab et al., 2010
Nanoplasmonic biosensor
Culture/ Urine
101 – 107 CFU/mL
300 CFU/mL
–
Chlamydia trachomatis
Soler et al., 2017
Leishmania spp
Electrochemical DNA biosensor
Genomic sequence of Leishmania major
0.5 – 20 ng/μL
0.07 ng/μL
–
DNA
Moradi et al., 2016
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