Systems and methods for airborne environmental detection and monitoring of pathogens using electrochemical analysis - Patents.com

Abstract

The present disclosure is directed to an airborne particle detection device, method, and system for analyzing environmental air samples and detecting airborne pathogens. The device includes an analysis vial and a biosensor electrode. The system further includes an external sampling device.

Description

[Technical field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to U.S. Provisional Application No. 63 / 363,055, filed April 15, 2022, the contents of which are incorporated herein by reference in their entirety.

[0002] Federally Sponsored Research and Development Statement This invention was made with government support under awards U01AA029331 and 1RF1AG064902 from the National Institutes of Health. The government has certain rights in the invention.

[0003] The field of the disclosure relates generally to devices, systems, and methods for surveying and detecting airborne pathogens. More particularly, the disclosure is directed to pathogen detection and monitoring of defined air spaces, such as small and large gathering spaces. [Background technology]

[0004] Coronavirus disease 2019 (COVID-19), first reported in December 2019, has infected 6.2 million Americans and caused 190,000 deaths in the United States and nearly 900,000 worldwide as of early September 2020 (according to the WHO website); the mortality rate is approximately 3%. Due to insufficient testing and an unknown number of asymptomatic individuals, the actual number of infections may be 6 to 24 times higher than reported. SARS-CoV-2 (CoV-2) is the virus underlying the disease, which in some patients results in a variety of symptoms, including fever, cough, nausea, and pain. In some cases, it can cause severe respiratory illness that impedes breathing, leading to hospitalization and death. However, many individuals are virtually asymptomatic but can shed virus comparable to symptomatic individuals and remain infectious. Unfortunately, even if a vaccine becomes available at the beginning of the new year, COVID-19 will likely continue to circulate well into 2021 and beyond. Finding new ways to detect this virus, as well as creating platforms for detecting other pathogens, will help limit the spread of viruses throughout communities during current and future pandemics.

[0005] The disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; CoV-2), which is transmitted from person to person by fomites or aerosols from contaminated surfaces. CoV-2 is transmitted from person to person by inhaling the virus through the mucous membranes of the nose and throat. This can occur by touching a fomites on a surface and then transferring the virus from the hands to the mouth and nose. However, airborne transmission is more prevalent. People shed the virus in respiratory secretions. The more intense the respiratory fluids are shed, the more virus is released, often further away. Thus, while speaking sheds relatively few viruses, yelling or singing produces more virus and over a wider area. Face coverings and masks are designed to limit the escape of respiratory droplets from infected individuals and to limit inhalation by other individuals.

[0006] Viruses reside in respiratory droplets and aerosols. Larger droplets carry more virus and fall to the ground faster, while aerosols are smaller, carry less virus, and travel greater distances. Particle size is also dynamic, often changing in size within the environment based on temperature and relative humidity (RH). Larger droplets can evaporate water and reduce their size similar to aerosols, while aerosols can pick up water and increase in volume in humid air. These are important factors when considering how far viruses can travel, as well as when designing means to collect and measure airborne viruses. Summary of the Invention [Problem to be solved by the invention]

[0007] A major obstacle in slowing the spread of CoV-2 is that asymptomatic individuals are contagious but have few or no symptoms. Detecting the virus rapidly (e.g., in real time or within seconds, minutes, or hours) could slow the spread in several dimensions. Thus, there is a need for rapid, noninvasive tests that detect viruses and other pathogens, even if individuals are asymptomatic, and allow for rapid contact tracing and isolation. [Means for solving the problem]

[0008] In one aspect, the disclosure is directed to an airborne particle detection device for analyzing an environmental air sample and detecting airborne pathogens, the device including: an analysis vial; and a biosensor electrode.

[0009] In another aspect, the present disclosure is directed to a method for detecting airborne pathogens, the method comprising: transporting a liquid sample from an external sampling device to an analysis vial of an airborne particle detection device; adding a hydraulic fluid to the analysis vial of the airborne particle detection device; detecting at least one pathogen; replenishing the external sampling device with sample fluid; and discharging the analysis sample from the analysis vial to a waste reservoir of the airborne particle detection device.

[0010] In yet another aspect, the present disclosure is directed to a system for detecting airborne pathogens, the system including: an airborne particle detection device; and an external sampling device.

[0011] In some embodiments, multiple pathogens can be detected simultaneously in a single test, the multiple pathogens being selected from a combination of viruses, bacteria, parasites, fungi, and molds, or multiple viruses, multiple bacteria, or multiple species or strains of viruses, bacteria, parasites, fungi, or molds. In some embodiments, multiple variants of a pathogen can be detected from a single test, the multiple variants including delta and omicron variants of SARS-CoV-2. In some embodiments, multiple pathogens are detected simultaneously in a multiplex test.

[0012] The embodiments described herein can be better understood by reference to the following description in conjunction with the accompanying drawings, in which: [Brief description of the drawings]

[0013] [Figure 1A]FIG. 1A is an exemplary embodiment of a SARS-CoV-2 biosensor design according to the present disclosure. The CoV-2 biosensor uses square wave voltammetry to measure the oxidation of tyrosine amino acids in virus particles. The oxidation releases electrons, which the sensor detects as a current. The biosensor uses nanobodies attached to a surface to provide specificity and concentrate the virus particles on an electrode for measurement. The electrode is blocked with albumin to limit non-specific signal. FIG. 1B is an exemplary embodiment of an air sampler and biosensor for continuous, real-time measurement of airborne pathogens (including CoV-2) according to the present disclosure. [Figure 1B] Same as above. [Figure 2A] 2A-2F show exemplary embodiments of affinity binding curves of isolated anti-SARS-CoV-2 RBD nanobodies according to the present disclosure. RBD-bound sensors were incubated with specific concentrations of purified candidate nanobodies for set times and allowed to associate (KON). The sensors were then transferred to a solution containing no nanobodies and allowed to dissociate over a time interval (KOFF). FIG. 2A shows the affinity binding curve for NIH-CoVnb-109. FIG. 2B shows the affinity binding curve for NIH-CoVnb-108. FIG. 2C shows the affinity binding curve for NIH-CoVnb-103. FIG. 2D shows the affinity binding curve for NIH-CoVnb-113. FIG. 2E shows the affinity binding curve for NIH-CoVnb-112. FIG. 2F is a table showing the 1:1 curve fitting used to calculate the KD of each nanobody. [Figure 2B] Same as above. [Figure 2C] Same as above. [Figure 2D] Same as above. [Figure 2E] Same as above. [Figure 2F] Same as above. [Figure 3A]3A-3B show an exemplary embodiment of NIH-CoVnb-112 specificity binding kinetics to ACE according to the present disclosure. FIG. 3A shows that SARS-CoV-1 RBD (blue open circle) and SARS-CoV-2 RBD (black open circle) were coated onto an ELISA plate at 10 micrograms / mL and incubated with a range of NIH-CoVnb-112 concentrations. Detection was performed using an anti-alpaca secondary antibody to confirm the lack of binding ability of NIH-CoVnb-112 to SARS-CoV-1 RBD. FIG. 3B shows that the CoV-2 RBD-coated ELISA plate was blocked with a non-specific protein and incubated with serial dilutions of each candidate anti-SARS-CoV-2 RBD nanobody. Biotinylated-ACE2 was added to each well and allowed to bind to the unoccupied RBD. The unoccupied RBD allowed a positive reaction signal that was suppressed in the presence of bound competitive nanobody. [Figure 3B] Same as above. [Figure 4] FIG. 4 is an exemplary embodiment of NIH-CoVnb-112 CoV-2 neutralization according to the present disclosure. To determine the neutralization activity of anti-SARS-CoV-2 nanobodies, FRNA50 assay was performed. Vero E6 cells (8×104 cells per well) were plated in 96-well Operetta compatible plates (PerkinElmer). Live CoV-2 virus + NIH-CoV2nb-112 dilutions were added to the 96-well plates and incubated for 24 hours. Cells were fixed and stained with SARS-CoV-2 anti-spike antibody followed by goat anti-rabbit IgG Alexa Fluor 594. Images were captured with an Operetta High Content Imager. [Figure 5A] 5A-5B show exemplary embodiments of Aβ oligomer standard curves according to the present disclosure. Examples of Aβ oligomer standard curves using synthetic Aβ dimers in MIE (FIG. 5A) and ELISA (FIG. 5B) with detection limits of 200 attograms / ml and 32 pg / ml, respectively. [Figure 5B] Same as above. [Figure 6A]6A-6B show an exemplary embodiment of a SARS-CoV-2 spike protein biosensor according to the present disclosure. The MIE biosensor is coupled with 100 μg / ml of NIH-CoVnb-112. Square wave voltammetry was used to detect CoV-2 RBD spike protein ranging from 2 fg / ml to 2 ng / ml (r2=0.9088). The study was performed in eight duplicates; a representative sensitivity curve (FIG. 6A) and oxidation peak (FIG. 6B) are shown. [Figure 6B] Same as above. [Figure 7] FIG. 7 is an exemplary embodiment of aerosol dynamics and residence time according to the present disclosure. Trajectories of 10 μm (green) and 100 μm (blue) particles emitted at an initial velocity of emission typical of a sneezing person. The dashed line indicates no evaporation, and the solid line represents evaporation of the particles upon emission to the atmosphere. The lifetime of the 10 μm particles increased from 8.3 minutes (no evaporation) to 12 hours (with evaporation), and the lifetime of the 100 μm particles increased from 4.9 seconds to 39.4 seconds. [Figure 8] 8 is an exemplary embodiment of a portable PalmSens4 potentiostat according to the present disclosure. The PalmSens4 potentiostat is equipped with graphite screen-printed electrodes. The device can be connected to a computer or run via Bluetooth on a smartphone. [Figure 9] FIG. 9 is an exemplary embodiment of a schematic diagram of an experimental setup for viral aerosol generation, environmental treatment, sampling, and characterization according to the present disclosure. [Figure 10]FIG. 10 is an exemplary embodiment of an atmospheric aerosol generation laboratory setup according to the present disclosure. Particle / gas streams (ambient, aerosolized, combusted, emitted, desorbed, or undesorbed) are sent through a cyclone, DMA, or Teflon filter for sample preparation. Variable humidity, O3 (plus options for VOC, SO2, NOx, NH3, or condensable organic aerosol addition, or sample replacement) inputs are combined with the sample in a Potential Aerosol Mass (PAM) reaction chamber to mimic atmospheric oxidation and photochemical processes. Oxidant levels are adjusted by varying the input O3, H2O, lamp voltage, and lamp type. The default lamp is low pressure Hg with a powerful 254 nm wavelength and an option for 185 nm by removing the quartz sleeve. [Figure 11] 11 is an exemplary embodiment of a laboratory aerosolization test chamber setup according to the present disclosure. The chamber is filled by aerosolizing the test particles / viruses at a constant nebulization rate. The concentration in the chamber is continuously monitored using a particle counter. Multiple PILS devices can be installed in the chamber and sample collected in parallel. [Figure 12] 12A is an exemplary embodiment of an airborne particle detection system according to the present disclosure, FIG 12B is an exemplary embodiment of an exterior view of a desktop airborne particle detection device according to the present disclosure, and FIG 12C is an exemplary embodiment of an exterior view of a duct air sampling airborne particle detection device according to the present disclosure. [Figure 13] FIG. 13 is an exemplary embodiment of a method for detecting airborne pathogens according to the present disclosure. [Figure 14] 14A and 14B are exemplary embodiments of the dimensions and boundary conditions of the hydrocyclone PILS according to the present disclosure. [Figure 15]FIG. 15 is an exemplary embodiment of the boundary conditions assumed for the numerical modeling simulations according to the present disclosure. [Figure 16] FIG. 16 is an exemplary embodiment of size-specific particle collection in a hydrocyclone based on a numerical modeling simulation according to the present disclosure. [Figure 17] FIG. 17 is an exemplary embodiment of a chamber experiment according to the present disclosure comparing the performance of commercial PILS (BioSampler® and LSS) and wet cyclone PILS for three aerosolized virus concentration levels: <500 copies / m3 (low), 500-10,000 copies / m3 (medium), and >10,000 copies / m3 (high). [Figure 18] FIG. 18 is an exemplary embodiment of PCR Ct values ​​(inverted y-axis) of indoor air samples collected using a hydrocyclone in an apartment with a SARS-CoV-2 positive patient and a control room according to the present disclosure. [Figure 19] Figure 19A is an exemplary embodiment of a laboratory characterization of a pAQ monitor to calculate SARS-CoV-2 variant-specific LoD according to the present disclosure. Figure 19B is an exemplary embodiment of proof-of-concept box plot data showing pAQ monitor oxidation current while sampling aerosolized inactivated CoV-2 according to the present disclosure. [Figure 20] FIG. 20 is an exemplary embodiment of a virus aerosolization experimental setup for determining pAQ sensitivity according to the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] The present disclosure describes an environmental sensor that detects aerosolized viruses in a given space (such as any indoor or enclosed space, including large spaces or other spaces with potentially shared airspace) to determine whether viral particles (such as aerosolized CoV-2) are present. Electrochemical, antibody-based biosensors for detecting inactivated viral particles of at least one respiratory virus (or multiple respiratory viruses) alternatively or additionally to SARS-CoV-2 viral particles are also described. In some embodiments, the biosensor detects at least one bacterial genus or species. In other embodiments, the device detects at least one parasitic, fungal, or mold genus or species.

[0015] Viral particles detectable by the disclosed biosensor include chikungunya, cholera, Crimean-Congo hemorrhagic fever, Ebola virus disease, Hendra virus disease, influenza (pandemic, seasonal, zoonotic), Lassa fever, Marburg virus disease, meningitis, MERS-CoV, monkeypox, Nipah virus disease, novel coronavirus (2019-nCoV), plague, Rift Valley fever, SARS, smallpox, tularemia, yellow fever, Zika virus disease, Ebola virus and Marburg virus (family Filoviridae); Ross River virus, Chikungunya avian encephalopathy (Family Filoviridae); Viruses, Sindbis virus, Eastern equine encephalitis virus (Togaviridae, Alphavirus), Vesicular stomatitis virus (Rhabdoviridae, Vesiculovirus), Amapari virus, Pichinde virus, Tacaribe virus, Junin virus, Machupo virus (Arenaviridae, Mammarenavirus), West Nile virus, Dengue virus, Yellow fever virus (Flaviviridae, Flavivirus); Human immunodeficiency virus type 1 (Retroviridae, Lentivirus); Moloney murine leukemia virus (Retroviridae, Gammaretrovirus); Insect deficiency virus type 1 (Retroviridae, Lentivirus); Influenza A virus (Orthomyxoviridae); Respiratory syncytial virus (Paramyxoviridae, Pneumovirus, Pneumovirus); Vaccinia virus (Poxviridae, Chordopoxviridae, Orthopoxvirus); Herpes simplex virus type 1, herpes simplex virus type 2 (Herpesviridae, Alphaherpesviridae, Simplexvirus); Human cytomegalovirus (Herpesviridae, Betaherpesviridae, Cytomegalovirus); Autographa californica nuclear polyhedrvirus (Baculoviridae, Alphabaculoviridae) (insect viruses); Ebola and Marburg viruses (Filoviridae); Semliki Forest virus, Ross River virus, Chikungunya virus, Onyong-nyong virus, Sindbis virus, Eastern / Western / Venezuelan equine encephalitis virus (Togaviridae, Alphavirus); Rubella (Rubella) virus (Togaviridae, Rubivirus); Rabies virus, Lagos bat virus, Mokola virus (Rhabdoviridae, Lyssavirus); Amapari virus, Pichinde virus,Tacaribe virus, Junin virus, Machupo virus, Guanarito virus, Sabia virus, Lassa virus (Arenaviridae, Mammarenavirus); West Nile virus, Dengue virus, Yellow fever virus, Zika virus, Japanese encephalitis virus, St. Louis encephalitis virus, Tick-borne encephalitis virus, Omsk hemorrhagic fever virus, Kyasanur Forest virus (Flaviviridae, Flavivirus); Human Hepatitis C virus (Flaviviridae, Hepacivirus); Human Immunodeficiency Virus Type 1 (Retroviridae, Lentivirus); Influenza A / B virus (Orthomyxoviridae, Common "flu" virus); Respiratory syncytial virus (Paramyxoviridae, Pneumovirus genus, Pneumovirus); Hepatovirus Ndola virus, Nipah virus (Family: Paramyxoviridae, Genus: Paramyxovirus, Henipavirus); Measles virus (Family: Paramyxoviridae, Genus: Paramyxovirus, Morbillivirus); Variola major (smallpox) virus (Family: Poxviridae, Chordopoxviridae, Orthopoxvirus); Human hepatitis B virus (Family: Hepadnaviridae, Orthohepadnavirus); Hepatitis delta virus (Hepatitis D virus) (Unassigned family, Deltavirus); Herpes simplex virus type 1, Herpes simplex virus type 2 (Family: Herpesviridae, Alphaherpesviridae, Simplexvirus); Human cytomegalovirus (Family: Herpesviridae, Betaherpesviridae, Cytomegalovirus), Adeno-associated virus Dependovirus, Parvoviridae Aichivirus Kobuvirus, Picornaviridae Australian bat Lyssavirus, Rhabdoviridae BK polyomavirus, Polyomaviridae Bannavirus Seadornaviridae Barma Forest virus Alphavirus, Togaviridae Bunyamwera virus Orthobunyavirus, Bunyaviridae Bunyavirus La Crosse Orthobunyavirus, Bunyaviridae Bunyavirus Snowshoe rabbit Orthobunyavirus, Bunyaviridae Cercopithecine herpesvirus Lymphocryptovirus, Herpesviridae Chandipura virus Vesiculovirus, Rhabdoviridae Chikungunya virus Alphavirus,Togaviridae Cosavirus A Cosavirus, Picornaviridae Cowpox virus Orthopoxvirus, Poxviridae Coxsackievirus Enterovirus, Picornaviridae Crimean-Congo hemorrhagic Nairovirus, Bunyaviridae Fever virus Dengue virus Flavivirus, Flaviviridae Dorivirus Thogotovirus, Orthomyxoviridae Dugbe virus Nairovirus, Bunyaviridae Duvenhage virus Lyssavirus, Rhabdoviridae Eastern equine encephalitis virus Alphavirus, Togaviridae Ebola virus, Filoviridae Echovirus Enterovirus, Picornaviridae Encephalomyocarditis virus Cardiovirus, Picornaviridae Epstein-Barr virus Lymphocryptovirus, Herpesviridae European bat lyssavirus, rhabdovirus GB virus C / G hepatitis virus Pegivirus, Flaviviridae Hantaan virus Hantavirus, Bunyaviridae Hendra virus Henipavirus, Paramyxoviridae Hepatitis A virus Hepatovirus, Picornaviridae Hepatitis B virus Orthohepadnavirus, Hepadnaviridae Hepatitis C virus Hepacivirus, Flaviviridae Hepatitis E virus Hepevirus, unassigned hepatitis delta virus Deltavirus, unassigned horsepox virus Orthopoxvirus, Poxviridae Human adenovirus Mastadenovirus, Adenoviridae Human astrovirus Mamastrovirus, Astroviridae Human coronavirus Alphacoronavirus, Coronaviridae Human cytomegalovirus, Herpesviridae Human enterovirus 68, 70 enterovirus, Picornaviridae Human herpesvirus 1 simplex virus, Herpesviridae Human herpesvirus 2 simplex virus, Herpesviridae Human herpesvirus 6 roseolovirus, Herpesviridae Human herpesvirus 7 roseolovirus, Herpesviridae Human herpesvirus 8 rhadinovirus, Herpesviridae Human immunodeficiency virus Lentivirus, Retroviridae Human papillomavirus 1 papillomavirus,Papillomaviridae Human papillomavirus 2 alphapapillomavirus, Papillomaviridae Human papillomavirus 16, 18 alphapapillomavirus, Papillomaviridae Human parainfluenza virus respiratory tract virus, Paramyxoviridae Human parvovirus B19 Erythrovirus, Parvoviridae Human respiratory syncytial virus Orthopneumovirus, Pneumoviridae Human rhinovirus Enterovirus, Picornaviridae Human SARS coronavirus Betacoronavirus, Coronaviridae Human spumaretrovirus Spumavirus, Retroviridae Human T-lymphotropic virus Deltaretrovirus, Retroviridae Human torovirus, Coronaviridae Influenza A virus Influenza virus A, Orthomyxoviridae Influenza B virus Influenza virus B, Orthomyxoviridae Influenza C virus Influenza virus C, Orthomyxoviridae Isfahan virus Vesiculovirus, Rhabdoviridae JC polyomavirus, Polyomaviridae Japanese encephalitis virus Flavivirus, Flaviviridae Junin arenavirus, Arenaviridae KI Polyomavirus, Polyomaviridae Kunjin virus Flavivirus, Flaviviridae Lagos bat virus Lyssavirus, Rhabdoviridae Lake Victoria Marburg virus Marburg virus, Filoviridae Langat virus Flavivirus, Flaviviridae Lassa virus Arenavirus, Arenaviridae Rosedale virus Norovirus, Caliciviridae Looping disease virus Flavivirus, Flaviviridae Lymphocytic choroiditis Arenavirus, Arenaviridae virus Machupo virus Arenavirus, Arenaviridae Mayaro virus Alphavirus, Togaviridae MERS coronavirus Betacoronavirus, Coronaviridae Measles virus Morbillivirus, Paramyxoviridae Mengo encephalomyocarditis virus Cardiovirus, Picornaviridae Merkel cell polyomavirus, Polyomaviridae Mokola virus Lyssavirus, Rhabdoviridae Molluscum contagiosum virus Morcypox virus,Poxviridae (Monkeypox virus) Orthopoxvirus, Poxviridae (Mumps virus) Rubulavirus, Paramyxoviridae (Murray Valley encephalitis virus) Flavivirus, Flaviviridae (New York virus) Hantavirus, Bunyaviridae (Nipah virus) Henipavirus, Paramyxoviridae (Norwalk virus) Norovirus, Caliciviridae (Ohnyong-nyong virus) Alphavirus, Togaviridae (Orf virus) Parapoxvirus, Poxviridae (Oropouche virus) Orthobunyavirus, Bunyaviridae (Pichinde virus) Arenavirus, Arenaviridae (Polio virus) Enterovirus, Picornaviridae (Punta Toro phlebovirus, Bunyaviridae (Pumala virus) Hantavirus, Bunyaviridae (Rabies virus) Lyssavirus, Rhabdoviridae (Rift Valley fever virus) Phlebovirus, Bunyaviridae (Rosavirus A) Rosavirus, Picornaviridae (Ross River virus) Alphavirus, Togaviridae Rotavirus A Rotavirus, Reoviridae Rotavirus B Rotavirus, Reoviridae Rotavirus C Rotavirus, Reoviridae Rubella virus Rubivirus, Togaviridae Sagiyama virus Alphavirus, Togaviridae Sarivirus A Sarivirus, Picornaviridae Sandfly fever Sicilian virus Phlebovirus, Bunyaviridae Sapporo virus Sapovirus, Caliciviridae Semliki Forest virus Alphavirus, Togaviridae Seoul virus Hantavirus, Bunyaviridae Simian foamy virus Spumavirus, Retroviridae Simian virus 5 Rubulavirus, Paramyxoviridae Sindbis virus Alphavirus, Togaviridae Southampton virus Norovirus, Caliciviridae St. Louis encephalitis virus Flavivirus, Flaviviridae Tick-borne Powassan virus Flavivirus, Flaviviridae Torque teno virus Alphatorque virus, Anelloviridae Tuscan virus Phlebovirus, Bunyaviridae Ukuniemivirus Phlebovirus, Bunyaviridae Vacciniavirus Orthopoxvirus, Poxviridae Varicella-zoster virus Varicellovirus,Herpesviridae Variolavirus Orthopoxvirus, Poxviridae Venezuelan Equine Encephalitis Alphavirus, Togaviridae Virus Vesicular Stomatitis Virus Vesiculovirus, Rhabdoviridae Western Equine Encephalitis Virus Alphavirus, Togaviridae WU Polyomavirus, Polyomaviridae West Nile Virus Flavivirus, Flaviviridae Yabasa Tumor U, Viruses include, but are not limited to, Orthopoxvirus, Poxviridae Yaba-like disease virus Orthopoxvirus, Poxviridae Yellow fever virus Flavivirus, Flaviviridae Zika virus Flaviviruses and viruses related to the Flaviviridae family.

[0016] Bacterial genera and species detectable by the disclosed biosensors include: Xanthomonas, Pseudomonas, Salmonella, Shigella, Chlamydia, Helicobacter, Yersinia, Bordatella, Pseudomonas, Neisseria, Vibrio, Haemophilus, Mycoplasma, Streptomyces, Treponema, Coxiella, Ehrlichia, Brucella, Streptobacillus, Fusospirocheta, Spirochete, Ureaplasma, Spirochete, Mycoplasma, Actinomycetes, Borrelia, Bacteroides, Trichomorus, Branhamella, Pasteurella, Clostridium, Corynebacterium, Listeria, Bacillus , Erysipelothrix, Rhodococcus, Escherichia, Klebsiella, Pseudomonas, Enterobacter, Serratia, Staphylococcus, Streptococcus, Legionella, Mycobacterium, Proteus, Campylobacter, Enterococcus, Acinetobacter, Morganella, Moraxella, Citrobacter, Rickettsia, Locrimea-related bacteria, as well as bacterial species such as: Pseudomonas aeruginosa, Escherichia coli, Burkholderia cepacia, Epidermidis, Enterococcus faecalis, Klebsiella pneumoniae, Staphylococcus aureus, Neisseria meningitidis, Moraxella pyogenes, Pasteurella multocida, Treponema pallidum, and P. mirabilis. Gram-negative bacterial genera and species detectable by the disclosed biosensors include, but are not limited to, Escherichia coli, Shigella, Salmonella, Campylobacter, Neisseria, Haemophilus, Aeromonas, Francisella, Yersinia, Klebsiella, Bordetella, Legionella, Corynebacteria, Citrobacter, Chlamydia, Brucella, Pseudomonas, Helicobacter, and Vibrio. Gram-negative bacterial genera and species detectable by the disclosed biosensors include, but are not limited to, Salmonella, Escherichia coli, Yersinia pestis, Klebsiella and Shigella, Proteus, Enterobacter, Serratia, and Citrobacter.

[0017] Fungi detectable by the disclosed biosensors include Cryptococcus neoformans; Blastomyces dermatitidis; Aieromyces dermatitidis; Histoplasma capsulatum; Coccidioides immitis; Candida spp., including C. albicans, C. tropicalis, C. parapsilosis, C. guilliermondii, and C. krusei; Aspergillus spp., including A. fumigatus, A. flavus, and A. niger; Rhizobium spp., including C. cereus, ... These include, but are not limited to, fungi related to the genera Trichophyton, Microsporum and Dermatophytes, as well as other yeasts and fungi currently known or later identified as pathogenic.

[0018] Parasites detectable by the disclosed biosensor include Anaplocephala, Ancylostoma, Necator, Ascaris, Brugia, Bunostome, Capillaria, Chavertia, Cooperia, Cyatostome, Silicosiculus, Chiricodontophorus, Chrycostephanus, Craterostomus, Dictyocaulus, Dipetalonema, Dipylidium, Dracunculus, Echinococcus, Enterobius, Fasciola, Filaroides, Habronema, Haemonchus, Metastrongylus, Moniesia, Nematodirus, Nipostrongylus, Hypertuberculosis, and Insects, Onchocerca, Ostertagia, Oxyuris, Parascaris, Schistosoma, Strongylus, Taenia, Toxocara, Strongyloides, Toxascaris, Trichinella, Trichuris, Trichostrongylus, Triodontphorus, Uncinaria, Ucheleria, Leishmaniasis, Human African Trypanosomiasis, Chagas Disease, Members of the phylum Apicomplexa, e.g. Babesia, Toxoplasma, Plasmodium, Eimeria, Isospora, Atoxoplasma, Cystoisospora, Hammondia, Besniotia, Sarcocystis, Frankelia, Haemoproteus, antigens from species of the genera Ustilago, Leucocytozoon, Theileria, Perkinsus and Gregarina; Pneumocystis carinii; members of the phylum Microspora, such as Nosema, Enterocytozoon, Encephalitozoon, Septata, Murazekia, Amblyospora, Amethon, Gurgea, Pleistophora and Microspora; and members of the phylum Acetospora, such as Haplospora, as well as species such as Plasmodium falciparum, Plasmodium vivax, Plasmodium ovale and Plasmodium malariae; Toxoplasma gondii; Leishmania amexicana, L. tropica, L. major, L. aethiopica, L. donovani, Trypanosoma cruzi, Trypanosoma brucei, Schistosoma mansoni, Schistosoma haematobium, Schistosoma japonicum; Trichinella spiralis; Wuchereria bancrofti; Brugia maleiri; Entamoeba histolytica; Enterobius vermicularis; Taenia solium, Taenia saginata, Trichomonas vaginalis, T hominis, T tenax; Giardia lamblia; Cryptosporidium parvum; Pneumonia carinii, Babesia bovis, B. divergens, B. microti, Isospora belli, L.Parasites associated with D. hominis; Dientamoeba fragilis; Onchocerca volvulus; Ascaris lumbricoides; Ancylostoma americanum; Ancylostoma duodenalis; Strongyloides stercoralis; Capillaria phipinensis; Angiostrongylus cantonensis; Hymenolepis nana; Diphyllobothrium latum; Echinococcus granulosus, Echinococcus multilocularis; Paragonimus westermani, P. cariensis; Clonorchis sinensis; Opisthorchis felineas, G. viverini, Fasciola hepatica, Sarcoptes scabiei, human lice, Phthylus puvis, and Dermatophytidae, as well as other parasites currently known to be pathogenic or that may later be identified as pathogenic.

[0019] Other pathogens detectable with the disclosed biosensors include Coronaviridae (e.g., MERS, SARS-CoV-2), Bunyavirus (e.g., Lassa, Junin, Rift Valley Fever, Andean, Sin Nombre, La Crosse, California Encephalitis, Crimean-Congo Hemorrhagic Fever), Filovirus (e.g., Ebola, Marburg), Flavivirus (e.g., Dengue, Zika, West Nile), Paramyxoviridae (e.g., Nipah, Hendra), Picornaviridae (e.g., EV-D68, EV-A71), Togaviridae (e.g., Chikungunya, EEE, VEE, WEE), Bacillus anthracis (gene (including genotypic resistance markers), Yersinia pestis (including genotypic resistance markers), Francisella tularensis (including genotypic resistance markers), Burkholderia spp. (including genotypic resistance markers), Botulinum toxins (including identification and differentiation of relevant serotypes), ESKAPE pathogens (including genotypic resistance markers) (e.g., Enterococcus, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacteriaceae), Lassa virus, Nipah virus, Rift Valley fever virus, Enterovirus D68 virus, Candida auris, Coccidioides spp., and novel coronavirus.

[0020] Aspects of the present disclosure are provided by the subject matter of the following clauses:

[0021] 1. An airborne particle detection device for analyzing environmental air samples and detecting airborne pathogens, comprising: analytical vials; and Biosensor Electrodes 13. An apparatus comprising:

[0022] 2. The device of the preceding clause, wherein the device is configured to be used to simultaneously detect multiple pathogens in a single test.

[0023] 3. The apparatus of any of the preceding clauses, wherein the plurality of pathogens is a combination of pathogens, each of the pathogens being selected from the group consisting of a virus, a bacterium, a parasite, a fungus, a mold, a plurality of viruses, a plurality of bacteria, a plurality of virus species or strains, a plurality of bacterial species or strains, a plurality of parasitic species or strains, a plurality of fungal species or strains, and a plurality of mold species or strains.

[0024] 4. A device according to any of the preceding clauses, used to test for multiple variants of a pathogen from a single test.

[0025] 5. The device of any of the preceding clauses, wherein the multiple variants of the pathogen include delta and omicron variants of SARS-CoV-2.

[0026] 6. An apparatus according to any preceding clause configured for use in multiplex testing.

[0027] 7. A device according to any preceding clause, wherein in said multiplex test, multiple pathogens are detected simultaneously.

[0028] 8. A method for detecting airborne pathogens, comprising: transporting the liquid sample from the external sampling device to an analysis vial in the airborne particle detection device; adding a working fluid to the analysis vial of the airborne particle detection device; Detecting at least one pathogen; Replenishing the external sampling device with sample liquid; and Discharging the analytical sample from said analytical vial into a waste reservoir of said airborne particle detection device. A method comprising:

[0029] 9. The method of the preceding clause, wherein detecting at least one pathogen includes simultaneously detecting multiple pathogens in a single test.

[0030] 10. The method of any of the preceding clauses, wherein the multiple pathogens are a combination of pathogens, each of the pathogens being selected from the group consisting of a virus, a bacterium, a parasite, a fungus, a mold, multiple viruses, multiple bacteria, multiple virus species or strains, multiple bacterial species or strains, multiple parasitic species or strains, multiple fungal species or strains, and multiple mold species or strains.

[0031] 11. The method of any of the preceding clauses, wherein detecting at least one pathogen comprises detecting multiple variants of the pathogen from a single test.

[0032] 12. The method of any of the preceding clauses, wherein the multiple mutants of the pathogen include delta and omicron mutants of SARS-CoV-2.

[0033] 13. The method of any of the preceding clauses, wherein detecting at least one pathogen comprises multiplex detection, wherein multiple pathogens are detected simultaneously.

[0034] 14. A system for detecting airborne pathogens, comprising: Airborne particle detection devices; and External Sampling Device Including, the system.

[0035] 15. A system as described in the preceding clause used to simultaneously detect multiple pathogens in a single test.

[0036] 16. The system of any of the preceding clauses, wherein the multiple pathogens are a combination of pathogens, each of the pathogens selected from the group consisting of a virus, a bacterium, a parasite, a fungus, a mold, multiple viruses, multiple bacteria, multiple virus species or strains, multiple bacterial species or strains, multiple parasitic species or strains, multiple fungal species or strains, and multiple mold species or strains.

[0037] 17. A system according to any of the preceding clauses, used to test for multiple variants of a pathogen from a single test.

[0038] 18. The system of any of the preceding clauses, wherein the multiple variants of the pathogen include delta and omicron variants of SARS-CoV-2.

[0039] 19. A system according to any preceding clause, configured for use in multiplex testing.

[0040] 20. A system according to any preceding clause, wherein multiple pathogens are detected simultaneously in the multiplex test. EXAMPLES

[0041] Without further elaboration, it is believed that one skilled in the art can, using the preceding description, utilize the present invention to its fullest extent. Thus, the following examples are to be construed as merely illustrative and not limiting of the disclosure in any way.

[0042] Immuno-based biosensors and environmental detection of airborne pathogens. In an exemplary embodiment, the biosensor is deployed in an environmental detector for rapid (e.g., real-time or near real-time) continuous measurement of sampled air. The disclosed environmental biosensor for detecting target organisms is surprisingly and unexpectedly based on ultrasensitive electrochemical techniques used in vivo (e.g., brain, tissue, interstitial fluid, etc.) for Alzheimer's disease research to detect macromolecular targets.

[0043] An early microimmunoelectrode (MIE) biosensor was developed to detect amyloid beta (Aβ) peptides in the setting of Alzheimer's disease. This electrochemical sensor uses voltammetry to measure the oxidation of tyrosine amino acids in proteins. Oxidation is the release of electrons that a carbon fiber electrode detects as a change in current. The amount of current is proportional to the amount of protein present. To provide specificity, the biosensor uses antibodies covalently bound to a surface to concentrate proteins to the electrode for measurement.

[0044] The biosensor of the present disclosure is based on a similar design to the MIE. In some embodiments herein, we describe a CoV-2 nanobody (produced in a llama) with 5 nM affinity for the SARS-CoV-2 repeat binding domain (RBD) of the spike protein and very high selectivity for the CoV-1 spike protein. The present disclosure demonstrates that the CoV-2 biosensor has an initial sensitivity of 2 fg / ml. In contrast, conventional antigen tests for CoV-2 are sensitive to the low pg / ml range. The development of the environmental sensors, biosensors, and methods disclosed herein included mimicking real-world environmental conditions, particularly atmospheric aerosol conditions, necessary to test and optimize the performance of the biosensor for field deployment.

[0045] As disclosed herein, the immuno-based electrochemical biosensor provides real-time and continuous measurement of CoV-2 aerosols for use in airborne environmental detection and diagnostics. In some embodiments, the sensor targets CoV-2. In other embodiments, the design and methodology is adapted to multiple pathogens present in the air or from breathing. The airborne particle detectors described herein monitor gathering spaces for environmental risks and alert the need for evacuation and / or enhanced disinfection.

[0046] In exemplary embodiments, the CoV-2 biosensor has reasonable sensitivity to recombinant spike protein and is adaptable depending on the viral (pathogen) particle, antibody type, lifetime, concentration, and orientation on the electrode surface. In some embodiments, the biosensor is applicable for inactivated CoV-2 viral particle detection. In these embodiments, specificity controls include other viral surface proteins and viral particles. Depending on the embodiment, the electrode design is optimized for the size and type of material that has the greatest impact on specificity and oxidation properties.

[0047] Airborne transmission of CoV-2 is caused by the spread of droplet nuclei (aerosols) that remain infectious even when suspended in the air over long distances and prolonged periods of time. Guided by observational studies of CoV-2 and other infectious viruses, the biosensor performance metrics of the present disclosure are systematically evaluated for sensitivity, detection limit, and lifetime, and aerosolized virus particles are subjected to relevant environmental parameters including relative humidity, temperature, and atmospheric residence time. Biosensor performance also includes testing under conditions mimicking real-world indoor and urban air, where aerosolized virus droplets are mixed with particulate matter contaminants such as volatile organics, dust, and soot. In some embodiments, an environmental sensor device sampling a given air space detects CoV-2 in real time or near real time over a period of at least about 12 hours to about 24 hours.

[0048] Diagnostic Testing. As discussed above, there is a need for increased and improved capabilities to test for pathogens, including CoV-2. While detection and diagnosis of both symptomatic and asymptomatic individuals is necessary to inform isolation and / or quarantine of individuals and reduce community spread, an equally important, yet less developed, countermeasure is real-time (or near real-time) monitoring of congregate areas for airborne viruses that may result in the closure of the space or warrant aggressive disinfection of the area. In some embodiments described herein, airborne pathogen sensors are used in conjunction with aerosol disinfectant misters for immediate cleanup to limit the spread of detected viruses and / or pathogens.

[0049] Traditional tests for CoV-2 generally detect RNA, antigens (the virus itself), or antibodies. Each of these tests varies by sensitivity / specificity, length of analysis time, or stage of disease. RNA and antigen tests are useful for detecting current virus, while antibody tests identify past infections. RT-PCR tests that detect RNA vary in reaction time from hours to days under best-case scenarios, while antibody tests generally take 1-2 days for results. Antigen tests tend to be the most rapid, and current saliva or nasal swab test results are returned in as little as 5 minutes using a portable sensor (e.g., Abbott COVID-19 ID NOW Test). However, blood tests require a trained person to draw blood, and saliva tests, while rapid and non-invasive, leave behind biological material that must be safely disposed of.

[0050] The sensitivity / specificity of conventional COVID-19 tests varies widely. RT-PCR tests tend to be the most sensitive, with an accuracy of up to 97.4% in clinical practice. In contrast, some serological antibody tests have a specificity of less than 50%, making these tests largely meaningless in clinical practice. In a meta-analysis, antigen tests vary widely in sensitivity up to 94%, but the average was a specificity of 99.5% (true negative) and a sensitivity of 56.2% (true positive). The advantage of conventional antigen tests is their fast turnaround time, but there is still significant room for improvement in diagnostics.

[0051] In addition to the personal diagnostic value of these tests, there is still a need to develop sensors for airborne environmental detection. Available tests for environmental viruses generally include surface swab tests or single-use repeated air sample measurements. Currently, no tests are available that provide user-free continuous measurements of airborne CoV-2 and / or other pathogens. The disclosed systems, devices, and methods for real-time detection of airborne environmental pathogens (including CoV-2) allow public places to be monitored to protect against outbreaks or "super-spreader" events for public safety.

[0052] Immuno-biosensor for aerosolized and airborne detection. Disclosed herein is an ultrasensitive immuno-based electrochemical biosensor for detecting pathogens, in an exemplary embodiment, the spike protein on the surface of CoV-2. The CoV-2 biosensor disclosed herein (FIGS. 1A-B) is applicable for detecting airborne viruses (and / or pathogens) using environmental sampling and detection systems applicable to large areas such as airports, hospitals, conference centers, or school venues. Depending on the embodiment, a specifically optimized biosensor is implemented, taking into account the deployment and lifetime conditions of sampling and monitoring. Depending on the embodiment, the collection platform can be modified to detect other pathogens and / or combinations of pathogens.

[0053] The system, method, and device innovations disclosed herein are based, at least in part, on immune-based biosensors, nanobodies that provide specificity, and / or sample collection and processing of aerosolized pathogen particles (e.g., CoV-2 viral particles) in real environmental conditions prior to testing with biosensors.

[0054] CoV-2 Biosensor. The microimmunoelectrode (MIE) technology disclosed herein uses square wave voltammetry to measure the oxidation of tyrosine amino acids in specific proteins. In CoV-2 biosensor embodiments, biosensor sensitivity has been observed down to 2 fg / ml of CoV-2 spike RBD protein, in contrast to conventional CoV-2 immunosorbent assays in the low pg / ml range (Figure 6). In some embodiments, the biosensor uses recombinant spike protein. In other embodiments, the biosensor uses CoV-2 viral particles.

[0055] As disclosed herein, specificity for the target is based on the antibody covalently bound to the electrode surface. Oxidation of the CoV-2 spike protein bound to the antibody was measured as a direct indication that the protein was present. Importantly, tyrosine oxidation is irreversible, so the protein bound to the antibody on the surface of the electrode is measured only once. This is in contrast to many conventional electrochemical sensors that measure impedance at the electrode surface, essentially measuring the binding event instead of the actual protein. Impedance measurements can be fraught with specificity issues, as non-specific proteins or molecules can deposit on the electrode surface, producing a signal often referred to as "fouling."

[0056] Anti-CoV-2 Nanobodies. Five anti-CoV-2 nanobodies were obtained from the camelid family (including llamas), which produce a subclass of IgG with unpaired heavy chain variable domains known as nanobodies. The nanobodies designed and described herein have been sequenced, and can therefore be rapidly and inexpensively grown in bacteria for mass production, and can be modified by recombinant molecular biology, as needed, for example to increase affinity or to orient at an electrode surface. Nanobodies are generally more robust than antibodies, surviving dehydration conditions and the large temperature ranges that can vary between sampling environments of the airborne particle detectors combined with biosensor electrodes described herein. The NIH-CoVnb-112 nanobody has an affinity of 5 nM and is much more selective for the CoV-2 spike protein than CoV-1 in an ELISA format (Figure 3A). Other nanobodies with lower affinities are also contemplated, depending on the embodiment and sampling environment (Figure 2F).

[0057] Airborne detection under realistic environmental conditions. Aerosol transmission is an important route of transmission for CoV-2 based on clinical observations in closed spaces. Currently, knowledge gaps exist regarding the aerodynamic properties and transmission routes of CoV-2 in aerosols due to challenges associated with sampling in real environments and quantification at various particle sizes and concentrations. These real-world factors have a direct impact on the integrity of the virus and its ability to be measured. Biosensor characterization includes a wide range of viral aerosol sizes and concentrations, including but not limited to various size distributions of viral aerosols corresponding to different modes of airborne release from speaking, coughing, and sneezing. Aerosol samples are injected into an environmental chamber to mimic their fate and transport in a real indoor environment containing pollutants. The biosensor development described herein encompasses a groundbreaking shift in our understanding of how environmental conditions alter airborne CoV-2 viral particles.

[0058] CoV-2 detectors. CoV-2 immune-based biosensors provide ultra-high sensitivity for real-time pathogen detection. In some embodiments, the sensors detect CoV-2. Other embodiments include similar sensors developed with antibodies against other pathogens in a multi-electrode array. Airborne particle detectors allow continuous, immediate feedback of viral threats in the environment. They can also alert areas for subsequent evacuation or enhanced disinfection. They can also be coupled with disinfectant aerosol sprays for immediate resolution to keep crowds safe in real-time and limit disruptions to ongoing activities. Importantly, airborne particle detectors alert that someone in the crowd is COVID-19 positive, hopefully justifying individual testing within the population for identification and isolation on a much larger scale than is currently possible.

[0059] Characterization of anti-SARS-CoV-2 nanobodies. Five anti-SARS-CoV-2 nanobodies were generated to detect the repeat binding domain (RBD) of the spike protein, as described above. Association and dissociation rates were determined by immobilizing the biotinylated RBD on a streptavidin-coated optical sensor using Biolayer Interferometry on a BioForte Octet Red96 system, and the KON and KOFF of each nanobody were determined (Figure 2A-E). Curve fitting using a 1:1 interaction model allowed the affinity constant (KD) to be measured for each nanobody, as detailed in (Figure 2F). Various embodiments of the CoV-2 biosensor include these nanobodies, as well as several commercially available monoclonal antibodies. One exemplary embodiment of the CoV-2 biosensor includes the nanobody NIH-CoVnb-112, which has the highest affinity (approximately 5 nM).

[0060] Direct ELISA was used to determine the binding of NIH-CoVnb-112 to SARS-CoV-2 RBD or SARS-CoV-1 RBD (Figure 3A). The nanobodies bound readily to the CoV-2 spike protein, whereas binding to CoV-1 was negligible at any nanobody concentration. Competitive binding assays demonstrate that these nanobodies are able to block CoV-2 binding to ACE2 (Figure 3B). NIH-CoVnb-112 produces maximal inhibition of ACE2 binding with an EC50 of 0.02 μg / ml (1.11 nM). NIH-CoVnv-112 was also used to neutralize live SARS-CoV-2 virus infecting Vero E6 cells in an FRNA50 assay (Figure 4), demonstrating the virus's ability to bind not only to the RBD protein but also to intact viral particles.

[0061] Anti-Aβ MIE biosensor. As described herein above, an ultrasensitive example of MIE technology includes the Aβ MIE, which was developed to detect oligomeric species using aggregate-selective antibodies attached to a carbon fiber electrode. The MIE detected Aβ dimers down to 200 attograms / ml (Figure 5A). In contrast, a commercially available ELISA for detecting this Aβ oligomeric target has a sensitivity of 32 pg / ml (Figure 5B). Similar success in improving sensitivity using the MIE was also observed for other target proteins such as Aβ40 and tau.

[0062] CoV-2 biosensor. The MIE was coupled with 100 μg / ml of NIH-CoV2nb-112 and then incubated with various concentrations of CoV-2 spike protein RBD. The biosensor was sensitive to 2.0 fg / ml of CoV-2 RBD spike protein and saturated above 200 pg / ml (Figure 6A-B).

[0063] Aerosol Dynamics and Residual Time. Airborne transmission includes both large particles and droplets (e.g., from talking, coughing, or sneezing) and small particles (e.g., from evaporation). Coupled governing equations of aerosol dynamics (e.g., droplet evaporation) and transport (diffusion, gravitational settling) were used to numerically determine the transport, resulting lifetime, and fate of droplets in the air. Figure 7 shows the horizontal travel distance for droplets in the size range of 10 μm (green) and 100 μm (blue) at 25% relative humidity. Due to evaporation, the released droplets decrease in size and their residual time, airborne lifetime, and horizontal travel distance increase. For example, a 10 μm droplet normally travels 10.9 m, but when it evaporates to 1.1 μm, it travels 48.6 m. Thus, the airborne particle detector disclosed herein is designed with a particle-into-liquid sampler (PILS) that can collect aerosol particles from 30 nm to 10 μm.

[0064] General Method Virus generation and inactivation. SARS-CoV-2 (2019-nCoV / USA-WA1 / 2020 strain) and A / Puerto Rio / 8 / 1934 (H1N1) viruses are propagated on Vero-E6 cells in a biosafety level 3 facility. The specificity of the viruses tested is notably consistent with other coronaviruses, including other strains. Three days after inoculation, the supernatants are collected and pooled from several different tissue culture flasks. A first sample is taken for quantitative RT-PCR analysis to quantify the number of genomes in the supernatant. A second sample is taken to quantify the infectious titer by focus-forming assay or plaque assay, according to protocols established in the laboratory. To inactivate SARS-CoV-2 in the tissue culture medium, the cultures are incubated with a 1:1000 dilution of beta-propiolactone (BPL) for 18 h at 4 °C. Viral inactivation is verified by focus-forming or plaque assay. This tissue culture fluid containing SARS-CoV-2 particles can be used immediately for testing. In another embodiment, purification of the viral particles proceeds via ultracentrifugation on a sucrose gradient. In these embodiments, visualization by electron microscopy is performed to ensure minimal aggregation of the viral particles that may be caused by ultracentrifugation, and further purification may be performed if necessary.

[0065] Target Sensitivity of CoV-2 Biosensors. Depending on the embodiment, the lower detection limit of the airborne particle detector biosensor for CoV-2 viral particles can vary based on the expected presence of CoV-2 particles in the sample. 75% of COVID-19 positive individuals have 10 5 of CoV-2 virus particles, 50% and 5% have 10 6 and 10 8 has particles.

[0066] Airborne CoV-2 detector. Exemplary embodiment of airborne viral load in a 10x10 meter room: The air in a well-ventilated room is replaced 5-6 times per hour (every 10 minutes). An individual can exhale 1ml of EBCs every 10 minutes or ingest 10ml of EBCs just by breathing. 5Each person exhales 1000 CoV-2 virus particles. Talking or coughing can increase viral shedding by 6,000-fold. Viruses from breathing are diluted throughout the room. A 10m x 10m x 2.7m room contains 270L of air. Over a 10-minute period, an infected individual in that 75% group will, at rest, ingest approximately 3.7 x 10 2 An airborne particle detector sampling 20 L of air over a 5-minute period can shed 1.5 × 10 CoV-2 virus particles per 0.5 ml of test liquid. 4 In other embodiments, the sensitivity of the detector is at least about 50 times lower, i.e., 6.0×10 2 Viral particles / ml can be achieved. Viral loads may be higher in poorly ventilated rooms or if the individual is in any form of activity.

[0067] In some embodiments, the sensitivity target of the airborne virus detector is 2×10 for the biosensor. 2 The amount of CoV-2 virus particles per ml is converted to a concentration of 2 × 10 2 Viral particles / ml equates to 36 fg / ml of spike protein. The disclosed CoV-2 biosensor is sensitive down to 2 fg / ml, already enabling the high sensitivity required for such a device. Depending on the embodiment, the biosensor design includes appropriate sensitivity, increased air flow rate, and / or longer sampling times to further increase the signal.

[0068] Statistical methods are described and outlined below. Where possible power calculations are used to establish sample size prior to the experiment, sample size calculations will instead be performed post hoc. All experimental groups and run order will be randomized. Where possible, blinded studies and / or blinded data analysis will be performed.

[0069] Optimization of CoV-2 immuno-based biosensor Immuno-based biosensor for detecting CoV-2. The micro-immunoelectrode (MIE) biosensor, previously developed as a platform for continuous measurement of Aβ peptides with high sensitivity and specificity, was adapted to develop an immuno-based biosensor for CoV-2 by attaching and incorporating CoV-2 specific antibodies / nanobodies onto the electrode surface. Detection is achieved by electroactivity of tyrosine (Tyr) amino acids contained in positions 352, 365, 369, 380, 396, 421, 423, 449, 451, 453, 473, 489, 495, 505, and 508 of the spike protein, which has a phenolic group that can be oxidized on the surface of a carbon-based electrode. The oxidation pathway of Tyr can release an average of three electrons, which is detected using a technique called square wave voltammetry (SWV), which measures the current at the working electrode while scanning the electrode potential over the range of 0 V to 1.0 V as a function of time. The advantage of SWV over impedance measurements is that a direct, rather than indirect, signal is obtained from the CoV-2 peptide itself. The voltammogram shows an increase / peak in the measured current due to the oxidation of electroactive species, with the location of the peak corresponding to the oxidation potential of the specific species. With a carbon-based electrode, Tyr oxidizes near a potential of 0.65 V. Although 0.65 V can cause oxidation of a variety of molecules, including all of the tyrosine neighborhood, the antibody covalently attached to the electrode surface provides specificity for a specific target such as CoV-2. For rapid and continuous monitoring over a period of time, the oxidation current peak is generated in less than 1 min. The height of the oxidation peak is proportional to the amount of protein on the electrode surface, making it possible to obtain a relative concentration measurement (Figure 6(A-B)). The increased specificity at the lower limit of detection reduces the false negative rate of the test. Monitoring the intrinsic electrochemical activity of the CoV-2 peptide allows for a direct, real-time (or near real-time), reagentless detection device, as shown in the devices, systems, and methods described herein.

[0070] Preparation of electrodes. In an exemplary embodiment, the biosensor is prepared by drawing a length of carbon fiber (5 μm diameter, GoodFellow, UK) into a glass capillary tube pulled to a fine tip using a pipette puller, the carbon fiber is attached to an insulated silver wire using conductive silver adhesive paste, sealed with heat shrink tubing, and cut to a length of 30-50 μm. To promote oxidation of tyrosine and binding of capture antibody, the microelectrodes are pretreated in PBS using a triangular waveform from 0 to 3 V at 70 Hz for 20 seconds, followed by holds at -0.8 V and 1.5 V. Activation of the carboxyl groups on the carbon fiber surface is achieved by applying a 0.4 M EDC and 0.1 M NHSS solution (Thermo Scientific, IL, USA) to form a semi-stable reactive amine NHS ester. The activated microelectrodes are placed in the antibody solution and incubated at room temperature for 10 minutes and then at 4 °C overnight. After antibody attachment, the biosensor is incubated with 0.05% ethanolamine to inactivate reactive amine sites, followed by blocking of nonspecific protein binding sites with 0.1% albumin.

[0071] CoV-2 biosensor. In an exemplary embodiment, the biosensor has excellent sensitivity to CoV-2 RBD spike protein (2 fg / ml; Figure 6 (A-B)), is adaptable to detect intact virus particles, antibody type and concentration, as well as improved material durability for the desired environmental monitoring application. Depending on the embodiment, the biosensor design is optimized based on specificity, sensitivity, and longevity for inactivated CoV-2 virus particles. Controls include surface proteins of other viruses, as well as other inactivated virus particles such as influenza H1N1, H3N2, and H5N1 and other coronaviruses. The biosensor can be further engineered to optimize durability and improve production throughput using commercially available products, such as screen-printed carbon-based microelectrodes compatible with the PalmSens4 (BASi) potentiostat. The PalmSens4 is portable and can be run on a smartphone, either connected to a computer via USB or via Bluetooth (Figure 8).

[0072] Antibody / nanobody optimization. As disclosed herein, specificity is achieved by using anti-CoV-2 antibodies immobilized on the electrode surface (Figure 1A), which facilitates the detection of trace amounts of CoV-2 by enriching peptides on the electrode surface. Although the specific properties of the antibody / antigen binding kinetics affect the performance of the biosensor so that it can be adapted and / or optimized for the desired sensor type, the selectivity of carbon fiber microelectrodes demonstrates that they can be used for several environmental sampling applications. For example, antibodies that bind CoV-2 with high affinity are useful for measuring low levels in samples. However, antibodies with weaker binding properties have the ability to release CoV-2 peptides after oxidation, which increases their effective use time. Evaluation of CoV-2-specific nanobodies, several monoclonal antibodies, and a control nonspecific nanobody helped to determine nanobodies that have the advantage of being more flexible in terms of orientation strategies and resistance to changes in environmental conditions compared to standard monoclonal antibodies.

[0073] Experimental Design. In some embodiments, a CoV-2 specific nanobody, two standard anti-CoV-2 monoclonal antibodies, and a control non-specific nanobody (raised against Aβ) with different binding properties (Figure 2F) are used to determine which is most effective for longevity of repeated measurements in the environmental detection sensor. Depending on the embodiment, two monoclonal antibodies (Invitrogen) that have shown specificity for CoV-2 may also be included. Each antibody is evaluated to determine optimal performance in solutions containing CoV-2 and CoV-1 spike proteins at high (100 μg / ml), medium (20 μg / ml), and low (4 μg / ml) coating concentrations, as well as to determine signal specificity in samples containing CoV-2 and H1N1 viral particles (n=5 electrodes / condition). The biosensor is designed to detect spike proteins from 100 pg / ml to 0.1 fg / ml and 10 to 10 4 The virus particles are tested using a control to ensure specificity and to determine the lower limit of detection. The specificity of the target is at least 10 × 10 with 90% specificity. 2 of CoV-2 virus particles (calculation and general methods are described elsewhere herein).

[0074] Statistical analysis. The limit of detection (LOD) and limit of quantification (LOQ) are calculated as 3 times the standard deviation of the measurements of blank samples, with a factor of 10 for the LOQ. Intra- and inter-assay coefficients of variance (CV) are calculated by the percent variation between replicate runs across the same electrodes within a sample and across electrodes with the same sample concentration. In some embodiments, only electrode / antibody concentrations that yield reliable CVs of less than 20% for both intra- and inter-assay variability are considered for further optimization. Specificity is determined by the lowest concentration at which measurements for CoV-2 are significantly greater (t-test p<0.05) than measurements with the same electrodes in the same concentration control. In an exemplary embodiment, the antibody with the best specificity / sensitivity is selected for optimization and / or adaptation of the electrode design.

[0075] As disclosed herein, high affinity antibodies will provide the highest sensitivity for trace detection in smaller spaces with time point (e.g., non-continuous) monitoring, while low affinity antibodies provide longevity for repeated (e.g., continuous) monitoring in environmental sensors. If the desired LOD or specificity at the LOD is not achieved using standard attachment protocols, recombinant molecular biology can be used to modify amino acids of nanobodies to orient them specifically when covalently attached to the biosensor surface.

[0076] Materials Optimization. In some embodiments, biosensors are prepared using carbon fiber microelectrodes. In other embodiments, biosensors are prepared using screen-printed carbon-based electrodes to provide more durable, low-cost electrodes for use in environmental monitoring devices. Screen printing of microelectrodes also allows flexibility in the materials used for the working electrodes, for example, incorporating carbon nanotubes or other nanomaterials to improve the analytical performance of the sensor.

[0077] The NIH-CoV2nc-112 nanobody has been successfully attached and detected by CoV-2 using commercially available screen-printed graphite electrodes (1 mm working diameter) connected to a portable PalmSens 4 potentiostat (Figure 8). In an exemplary embodiment, this electrode design has been miniaturized to increase sensitivity for use in sampling and / or monitoring devices.

[0078] Experimental design. Graphite working electrodes with Ag / AgCl reference and counter electrodes are screen printed with working diameters of 50 μm, 100 μm, and 300 μm. Screen printed electrodes are tested with optimized antibodies / nanobodies attached to determine LOD and lifetime for each working electrode size (n=5 electrodes / size). As above, results for LOD and LOQ are evaluated for each working electrode size to determine optimal sensitivity. To assess lifetime, electrodes of each size are tested with continuous sampling of low or high concentrations of CoV-2 spike protein (SWV scan every 60 seconds) to determine reliability cutoff. When measurements start to fluctuate more than 2 standard deviations from the starting point, the sensor is considered unreliable.

[0079] Smaller size working electrodes provide greater sensitivity to low levels of CoV-2 protein and are useful for smaller sampling spaces and / or non-continuous (e.g., sparse and / or randomized time point samples) monitoring, while larger size electrodes provide extended (e.g., continuous sampling) life useful for environmental monitoring systems. In embodiments where screen-printed graphite electrodes are found not to produce the desired level of sensitivity for CoV-2 detection as glass-encapsulated carbon fiber microelectrodes, carbon nanotubes are incorporated into the electrode ink to enhance electron transfer and minimize electrode fouling. Another embodiment may include reinforcing the carbon fiber design by encasing the glass seal with epoxy resin. In embodiments where the sensor life is found not to exceed 8-12 hours (a time limit determined to minimize repeated sensor replacement), the time between sampling measurements is extended to determine whether this extends the reliability of the sensor. Criteria for electrode sensitivity, specificity, and reliability are described elsewhere herein.

[0080] Environmental detection of airborne CoV-2 SARS-CoV-2 is transmitted through several modes, including aerosols and droplets that remain suspended in the air long enough to be inhaled. When aerosols and droplets containing respiratory fluids and microorganisms are expelled into unsaturated air, or air with less than 100% relative humidity (RH), they evaporate partially or completely to equilibrate with ambient conditions. As shown in Figure 7, this process reduces particle size, resulting in longer airborne lifetime. Evaporation also increases the free H+ ion concentration in the aerosol and decreases the pH, while solutes such as salts and proteins remain intact. The interplay of salts, changing pH, temperature, and RH in the shrinking droplets is dynamic. Enveloped viruses such as SARS CoV-2 that divide on aerosol surfaces can suffer damage from increased surface tension, shear stress, and conformational rearrangements driven by this dynamic interaction. Peptide unfolding and subsequent protein denaturation can occur at the air-water interface of the droplet. Therefore, proper consideration of environmental parameters such as RH and temperature is necessary in determining biosensor design, especially as they affect the infection dynamics of the virus (e.g., size, persistence time, distance traveled) and subsequent detection of the virus after it is excreted from an infected person into the aerosol phase. Recovering and measuring the virus encapsulated in the aerosol phase under various environmental conditions is important in building devices to detect viral particles (e.g., CoV-2 viral particles) in various environments and conditions.

[0081] As described herein, aerosolization of inactivated SARS-CoV-2 suspension into an exemplary system embodiment (Figure 9) served to address i) the effects of aging and environmental treatments (RH, temperature, and residence time) on sensitivity, detection limit, and lifetime (number of measurements), and ii) the impact of sensor performance from airborne particulate matter contaminants mixed with the virus. For bioaerosol aging studies, a combination of the following was used to realistically simulate conditions in the natural air environment: a) A reaction test chamber (rotating drum) with temperature and RH control capabilities to hold particles in the air for a significant period of time (up to 24 hours); b) an aerosol generator that generates an aerosol and sprays it onto the drum; and c) Instrumentation for measuring particle size and particle number concentration, as well as sampling of particles into a liquid medium for off-line injection into a biosensor.

[0082] Aerosol generation. A three-jet Collison nebulizer (Biaera Technologies, LLC) operating at a pressure of 40 psi and a total flow rate of 12-L per minute (L / min) was used for aerosol generation. Droplet size distributions were generated that mimicked the three situations of viral droplet emission: exhalation (breathing), sneezing, and coughing (see Table 1).

[0083] [Table 1]

[0084] For various embodiments described herein, the aerosol contains vehicle (saline), inactivated CoV-2 viral particles, control viral particles (H1N1, H3N2, and H5N1), or a combination of CoV-2 and other viruses. The amount of viral particles is varied in the solution between 10 / ml and 106 / ml to mimic a wide range of viruses from an infected individual.

[0085] The nebulized viral aerosol airflow first enters the Aerosol Capacitance Chamber (ACC), which allows for droplet mixing and initial evaporation before entering the rotating drum. HEPA filtered air is used as the transport medium for the generated aerosol from the ACC to the drum. The aerosol-laden air is then mixed with clean air that is humidified using a Nafion dryer (Perma Pure LLC, PD-50T-24) to control the RH humidity in the chamber to precise levels. Controlling the ratio of clean humidified air to dry aerosol-laden air produces the desired RH conditions at various levels of subsaturation. The final conditioned airflow is introduced into the drum at a flow rate of 10 Lpm.

[0086] Rotating Drum. Rotating drums have been used to maintain and study bioaerosol populations entrained in air parcels for up to several days. Briefly, the rotating drum design described herein is a 55.5 L aluminum cylinder with an inner diameter of 35.6 cm and a wall thickness of 0.48 cm that rotates around a fixed central axis. The central axis is constructed of clear acrylic and is divided into two concentric sections. The inner axis conveys the conditioned aerosol-laden air in and out of the drum, while the outer axis acts as a wire chase to secure the instrumentation to a fixed mount on the axis. The target RH within the drum is achieved by adjusting the flow rates of aerosol, dry air, and saturated air. An RH probe (HP-22A; Rotronic) continuously monitors the RH within the drum. A temperature sensor probe located at the bottom of the right panel on the front of the enclosure is connected to a temperature control module, allowing the temperature to be adjusted and maintained in the range of 8 °C to 45 °C. In the center of the central axis is a UV light socket for a UV-C lamp emitting at 254 nm. The lamp is inserted into the aerosol chamber at the center of rotation and can radiate at a 360° angle.

[0087] Particle-Liquid Sampler. Solvent-soluble aerosols are collected using a particle-liquid sampler (PILS) prior to virus detection by a biosensor. There are several means of collecting aerosol particles into a liquid solution (e.g., impactor, condenser, etc.), and the choice of collection technique determines the size of the aerosols collected. Normal exhalation produces aerosols in the 0.03-10 μm range, but the size of the aerosols changes based on the environmental conditions before collection in the CoV-2 detector. It is therefore important to use the appropriate technique to capture as wide a range of aerosols as possible.

[0088] A custom PILS was designed to use a "wet cyclone" technique for particle collection. This technique ensures sampling of ambient aerosols in the aerodynamic size range of 0.03-100 μm. The wet cyclone PILS operates over a wide range of flow rates (50-1000 liters per minute) and user-defined sample collection times (can be as short as 5 minutes). However, operating the wet cyclone PILS at lower flow rates can affect overall device performance, as the particle collection efficiency of the wet cyclone depends on the flow rate and inlet air velocity. The wet cyclone (Figure 12A) is connected to a high-flow vacuum pump to sample air at approximately 1,000 (±10%) liters per minute (lpm). Prior to air sampling, the cyclone is filled with a predefined volume (approximately 15 ml) of phosphate-buffered saline (PBS) solution. The pressure drop causes ambient air to be rapidly sucked in through the tangential inlet, creating a vortex that creates a spinning film of PBS liquid on the inner wall of the cyclone. Aerosols entering the wet cyclone impact the inner wetted wall and are collected in the liquid medium. Aerosols not captured by the wet cyclone are exhausted from the top and captured by the HEPA filter. The air is sampled for 5 minutes, after which the concentrated particles collected inside the PILS are transferred to a biosensor using an automated liquid delivery system for eventual SARS-CoV-2 detection. The PILS has a built-in automatic HOCl decontamination function that decontaminates the entire device before dismantling or shutting down. This self-decontamination function ensures that users are not exposed to any potentially hazardous bioaerosols collected inside the PILS.

[0089] Test protocol. Virus or biosphere laden aerosols are continuously introduced into the chamber for 30 min to achieve various degrees of aerosol particle number size concentration (between 102 and 105 particles per liter). Aerosol concentration is monitored using an aerosol number size distribution measurement device - Electrical Low Pressure Impactor (ELPI; Dekati). Once a threshold concentration is reached, aerosol is sampled from the drum using a filter and a PILS sampler. Measurements are repeated approximately every half hour, and air is not evacuated from the drum between sampling periods. Once the sample measurement is finished, the chamber is evacuated at 40 L / min with dry HEPA filtered air until no particles are detected using the ELPI before starting a new sample.

[0090] Regarding the effect of aging and environmental treatments (RH, temperature, and remaining time) on the sensor performance in terms of sensitivity, detection limit, and lifetime (number of measurements). Relative humidity is varied over a wide range from 20% to ~100% in 10% increments, with each step lasting 30 minutes. At each step, air is sampled at 1, 5, and 10 minute increments to test the sensitivity of the biosensor. Previous studies have observed a clear U-shaped pattern regarding the relationship between RH and viral droplet viability. The virus appears to be most viable at both low RH (below 40%) and very high RH (above 90%), but decays significantly at intermediate RH.

[0091] Temperature is varied from 10°C to 50°C to mimic real-world conditions. When the first COVID-19 outbreak was reported, temperatures in Wuhan, China, were approximately 17°C in the morning and 8°C at night. In tropical countries where the disease persisted, temperatures exceeded 40°C. A recent molecular dynamics simulation study showed that temperature is a critical variable, as the spike glycoprotein responds differently under hot and cold conditions.

[0092] Regarding the impact of mixing viral aerosols with airborne particulate matter contaminants on sensor performance. Airborne viruses and particulate matter air contaminants interact to affect virus stability and infectivity. Contaminant particles may also act as carriers that can have complex adsorption and toxic effects on pathogens. Laboratory-generated particulate matter contaminants such as 1) ammonium sulfate (emitted from automobiles and power plants), 2) secondary organic aerosols (emitted from volatile organic compounds (VOCs) in urban indoor environments), and 3) primary organic aerosols (POA; emitted from wildfires) are introduced into the ACC (shown by dashed lines in Figure 10) in parallel with the nebulized viral aerosol airstream.

[0093] The setup of an exemplary system embodiment for generating air-relevant aerosols is summarized in schematic form in Figure 10. The novel exhaust / combustion chamber is designed and constructed to allow for combustion or thermally driven exhaust of organic gases and particles from desired source inputs (e.g., biogenic, urban, wildfire). Within the exhaust / combustion chamber, separate sub-chambers are available that allow for combinations of sources to mimic complex environments at different ratios. The resulting sample air stream is sent to either a cyclone, a Differential Mobility Analyzer (DMA) to deliver monodisperse aerosols, or a Teflon filter to remove particles for further control of the environment. The resulting primary sample (gas or particles) is enriched with various other pure components (e.g., SO2, NO2, NH3, NH4, NH4, NH5, NH6, NH7, NH8, NH9, NH4, NH4, NH4, NH5, NH6, NH7, NH4, NH4, NH4, NH5, NH6, NH7, NH4, NH4, NH4, NH4, NH5, NH6 ... x There is also the option to mix with CO2 (NH3, anthropogenic or biogenic VOCs). The advantage of this setup is that it can create any combination of gas and particle inputs from any source type or mixture of source types that can contribute to air emissions, and also works directly with outside air if required.

[0094] An exemplary system embodiment setup for generating laboratory inactivated virus aerosols is summarized in schematic form in Figure 11. A novel exhaust / combustion chamber has been designed and constructed to allow aerosolization and mixing of different test aerosols. The advantage of this setup is that multiple PILS can be used to sample air for direct parallel intercomparison studies.

[0095] CoV-2 biosensor for airborne detection. In an exemplary embodiment, the CoV-2 biosensor includes an optimized electrode as described above. Also, as described above, 75% of individuals with COVID-19 have 10% or more of the virus in 10 minutes of normal breathing. 5 The airborne particle detector described herein, which samples 20 L of air for 5 min, releases 1.5 × 10 virus particles per 0.5 ml of test liquid. 4 In another exemplary embodiment, the 50-fold lower sensitivity is 6.0×10 2 The target sensitivity is 100% virus particles / ml or is designed for airborne particle detectors. The conditions required for the biosensor to detect CoV-2 or negative control virus are focused on the length of collection time (5 minutes, 10 minutes, or 20 minutes of air). Increasing the length of time improves sensitivity but may reduce the frequency of measurements. For a given collection rate, repeated measurements determine the life of the biosensor. Exemplary embodiments include electrodes that continuously measure at the target sensitivity for a minimum of 12 hours, preferably 24 hours. In some embodiments, the target specificity to exclude other viruses is greater than about 85%, greater than about 90%, greater than about 95%, or greater than about 99%.

[0096] To correct for aerosol losses due to gravitational settling and dilution during aging, a mass balance equation is used, assuming first order decay for both processes in the drum. It has been observed in past experiments that charge generation due to drum rotation causes particle losses. To circumvent this problem, a small polonium source (Amstat Industries, 2U500) is inserted inside the drum on the axis to provide additional ions for neutralization, and grounded copper strips are added along the support wheel track inside and outside the drum chamber to conduct the charge generated by the drum rotation to ground. In the event of drum failure, an environmental chamber (5518; Electro-Tech Systems) is used, operated at room temperature (22 °C) and the same RH values ​​as listed above for the aerosol experiments. The PILS collector is subject to noise and drift, which must be corrected initially, if necessary.

[0097] An airborne CoV-2 biosensor must have both sensitivity and lifetime for repeated measurements. If necessary, sensitivity can be adjusted by using antibodies with different affinities, by changing the antibody concentration on the electrode surface, or by adjusting the air sample time. Lifetime is often a factor of antibody affinity; decreasing affinity can be achieved by using different antibodies or utilizing targeted mutations of nanobodies to alter the binding properties.

[0098] Method and apparatus for interfacing an ambient aerosol sampler to an electrochemical biosensor for detecting airborne pathogens - Patents.com As disclosed herein, a novel method has been developed that interfaces an electrochemical biosensor and an aerosol-liquid sampler, referred to as a pathogen Air Quality (pAQ) monitor. Deployment of this method embodies a rapid (e.g., real-time or near real-time) continuous airborne pathogen (e.g., viruses, bacteria, fungi, molds, and / or parasites, including coronaviruses and / or other respiratory viruses) detector for monitoring indoor spaces, including large indoor spaces. In some embodiments, the airborne detection system detects SARS-CoV-2. In other embodiments, the airborne detection system detects coronaviruses, including influenza. In still other embodiments, the airborne detection system detects at least viruses, bacteria, fungi, molds, and / or parasites.

[0099] In an exemplary embodiment, a proof-of-concept device called a pathogen air quality (pAQ) monitor (FIG. 11), which includes a wet-wall cyclone, was coupled to an automated liquid handling unit and an MIE detection unit that houses an MIE biosensor assembly (FIG. 11). The pAQ monitor's built-in decontamination feature allows for contactless system decontamination and ensures safe handling of the device.

[0100] In at least one exemplary embodiment, the device is a desktop instrument (FIG. 11B). A touch screen interface on the front panel includes data regarding electrode status (time until replacement, presence of virus, etc.), fluid levels, pump activity, and external variables such as temperature and humidity. Some embodiments further include compactness to reduce power and fluid consumption and facilitate installation in areas where space may be limited.

[0101] In at least one exemplary embodiment, the device is an air duct sampling unit (FIG. 11B). A front panel touch screen interface includes data regarding electrode status (time until replacement, presence of virus, etc.), fluid levels, pump activity, and duct air flow variables such as temperature and humidity. Some embodiments further include compactness to reduce power and fluid consumption and facilitate installation in areas where space may be limited.

[0102] Internally, the disclosed system consists of a pump-driven fluidic network with internal reservoirs for make-up and waste fluids (Figure 11). Specially prepared electrodes are located within the analysis vials and are electrically connected to a custom-programmed OEM electrometer. The pumps are controlled by an internal computer that also updates and responds to the user interface.

[0103] In some embodiments, the method (1300, FIG. 13B) includes transporting a liquid sample from an external sampling device to an analysis vial of the airborne particle detection device 1302. The liquid sample is pumped from the external aerosol-liquid sampler into the analysis vial (FIG. 14).

[0104] The method 1300 further includes adding 1304 hydraulic fluid to the analysis vial of the airborne particle detection device. Additional hydraulic fluid is added (if necessary) to the analysis vial (FIG. 15). 2. If a virus is present, the method 1300 further includes detecting 1305 the at least one pathogen. A reaction occurs and the electromagnetometer records a signal from the electrodes. The user interface updates and, if necessary, displays an alarm that is also displayed on the network output.

[0105] The method 1300 also includes replenishing the external sampling device with sample fluid 1306. The sample fluid is replenishing the sampler (FIG. 16).

[0106] The method 1300 further includes discharging 1308 the analysis sample from the analysis vial to a waste reservoir of the airborne particle detection device. After the sample is analyzed, it is discharged into the waste reservoir. If no virus is detected, sufficient working fluid is added to the analysis vial to maintain the electrodes.

[0107] In this embodiment, it takes approximately 5 minutes for the electrodes to analyze the sample while the external sampler collects the next sample. Depending on the embodiment, it may take less than about 10 minutes, less than about 5 minutes, less than about 4 minutes, less than about 3 minutes, less than about 2 minutes, or less than about 1 minute for the electrodes to analyze the sample.

[0108] Numerical simulation of a PILS hydrocyclone for theoretical particle collection efficiency calculations. In high-flow cyclones, particle separation relies on the swirling flow pattern of the inflowing particles. The swirling airflow causes the particles to collide with the cyclone walls, facilitating particle separation. The flow conditions inside the cyclone are highly turbulent and highly anisotropic. The carrier phase is gas (ambient air) and the dispersed phase is particles (water-liquid). Ansys Fluent 2021 R1 was used to perform the numerical simulations. The Reynolds stress model was applied to model the flow field inside the cyclone body.

[0109] The solution algorithm used to solve the pressure coupled equations is "SIMPLE" and the spatial discretizations applied are: "PRESTO!" discretization for pressure, "QUICK" method for momentum equations, second order upwind for turbulence equations, and first order for Reynolds stress terms. ICEM-CFD was used to create a structured hexahedral mesh for the cyclone design.

[0110] Figure 14A shows the dimensions and Figure 14B shows the computational domain of the simulated wet cyclone. The volumetric flow rate at the cyclone inlet was set to 1000 lpm (corresponding to an inlet velocity of 66.138 m / s). The boundary conditions assumed in this simulation are summarized in Figure 15. A thin liquid film was assumed to form along the cyclone walls, as shown in Figure 14B. The bottom (50 mm) of the wet cyclone was assumed to be filled with liquid (based on experimental observations). It is assumed that particles that come into contact with the cyclone wall (cone section) or the liquid surface at the cyclone bottom are trapped. The average volumetric mass between the inlet and outlet was monitored during the simulation to ensure that the mass between the inlet and outlet is equal. Figure 16 shows the particles trapped in the wet cyclone with sizes ranging from 0.1 to 5 μm. The numerical model results show that the wet cyclone has a collection efficiency of over 95% for particles larger than 1 μm and a cutoff diameter of 0.4 μm (where the collection efficiency is 50%).

[0111] PILS wet cyclone aerosol sampling performance in the laboratory: Chamber aerosolization experiments Wet cyclone virus sampling performance was compared with two commercially available PILS: BioSampler® (SKC Corporation, USA) and Liquid Spot Sampler™ (LSS; Aerosol Devices, USA). Inactivated Washington strain (WA-1) of SARS-CoV-2 virus was injected into a well-mixed 21 ml 3A PILS intercomparison experiment was conducted by aerosolizing in a sealed stainless steel test chamber at 1000 rpm (Figure 11). The wet cyclone, LSS, and BioSampler® were set to simultaneously sample the air in the chamber for 10 minutes. Note that while the high flow wet cyclone requires less than 5 minutes of sampling for virus detection, the chamber experiment was run for 10 minutes to ensure sufficient virus concentrations were collected in the BioSampler® and LSS for RT-qPCR analysis. Following sampling, RT-qPCR was used to quantitate the virus collected in each device. To investigate the effect of initial virus concentration on sampling performance, three virus load conditions were performed: <500 copies / m 3 ("Low"), 500-10,000 copies / m 3 ("medium"), and >10,000 copies / m 3 ("High") chamber experiments. All experiments were performed in duplicate or triplicate.

[0112] Figure 11 shows the 21m 3 The basic layout of the chamber experimental setup is shown. A 100ul aliquot of stock virus was thawed and diluted with PBS to the desired concentration. A Collison nebulizer (CH Technologies, USA) filled with inactivated WA-1 (diluted with PBS) was placed in one corner of the chamber. The outlet of the nebulizer was approximately 3 feet above the ground. Two fans were placed at opposite corners of the chamber (fan height = 1-1.5 feet) to achieve uniform mixing within the chamber. The wet cyclone and BioSampler® were placed approximately in the center of the chamber, but far enough apart to not interfere with either sampling collection (chamber floor area: 7.13 m). 2or 11 ft x 7 in). The stainless steel test chamber has multiple welded stainless steel ports (1 / 4 in (6.35 mm) diameter) that can be connected to external air sampling devices for chamber air sampling. One of these sampling ports was connected to the LSS and the other to a Scanning Mobility Particle Sizer (SMPS; TSI, USA). All sampler inlets were ensured to be at similar heights so that all instruments sampled the air at the same height (4 to 4.5 ft (121.92 to 137.16 cm) above the floor).

[0113] Experimental procedure (1) Chamber cleaning: The exhaust fan shutter was fully opened to allow maximum ventilation. The vertical HEPA fan filter (80 CFM, 99.97% particle removal) was switched on to filter out all particles suspended in the chamber. The chamber was cleaned for 60 minutes before the start of every experiment. The particle size distribution and particle number concentration (PNC) in the chamber were continuously monitored using the SMPS. (2) The Collison nebulizer filled with the stock virus was connected to a 20 psi compressed particle-free air supply. The nebulizer was left running for 5 minutes to obtain a stable aerosol generation. (3) After 5 minutes, all three samplers were switched on and air sampling was performed for 10 minutes. (4) After 10 minutes of sample collection, the three samplers and the Collison nebulizer were turned off. Step 1 was repeated and the PNC was monitored using the SMPS. (5) Once the PNC reached the original background concentration, the door to the chamber was opened, samples were collected, and stored in a 4°C refrigerator for RT-qPCR analysis. All RT-qPCR PCR analyses were completed within 18 h of sample collection.

[0114] Wet Cyclone PILS Virus Recovery FIG. 17 compares virus recovery rates of the wet cyclone in a closed chamber with BioSampler® and LSS at low, medium, and high concentrations of aerosolized WA-1. After 10 minutes of sampling, viral RNA concentrations (i.e., RNA copies / ml of collected medium) measured by the wet cyclone were on average 13-fold and 66-fold higher than those measured by BioSampler® and LSS, respectively. Interestingly, under low concentration conditions, WA-1 RNA was only recovered by the wet cyclone, whereas samples collected in BioSampler® and LSS were too low to be quantified by RT-qPCR. The high RNA recovery rate by the wet cyclone was due to the fact that BioSampler® (approximately 0.125 ml) was used for the 10-minute sample collection. 3 ) and LSS (approx. 0.015m 3 ), compared to a larger volume of air (approximately 10 m 3 This characteristic makes the wet cyclone ideal for use in hospitals and patient isolation rooms, where airborne virus concentrations range from 2 to 94,000 copies / m. 3 The present invention is ideal for use in high temporal resolution continuous monitoring applications in real-world environments where the temperature, humidity, and other aspects may vary over a range of 100-200°C.

[0115] Viral aerosol sampling performance in infected houses The wet cyclone assembly (cyclone, vacuum pump, and PBS solution) was transported to the apartments of two volunteers who tested positive for SARS-CoV-2. Volunteers collected 5-min air samples (n=3-4) from within their bedrooms / apartments, which were then stored on ice in 15 ml centrifuge tubes. The liquid samples were then transported to the laboratory and analyzed using RT-qPCR to detect the presence of SARS-CoV-2.

[0116] All seven air samples collected using wet cyclones in two apartments where SARS-CoV-2 patients lived tested positive based on RT-qPCR (Figure 18). The RT-qPCR results of the bedroom samples were compared to air samples collected from virus-free control rooms. The Ct values ​​of the air samples from the infected houses ranged from 32.7 to 34.9. Meanwhile, no virus was detected in the control air samples (concentration < instrument LoD). Significantly lower Ct values ​​were observed in the apartment air samples compared to the control air, indicating the possible presence of SARS-CoV-2 in the apartment air.

[0117] pAQ Monitor LoD The LoD of the pAQ monitor was calculated using the SARS-CoV-2 strain-specific biosensor LoD data described above, normalized by the volume of air sampled per ml of liquid collection medium. Figure 19A shows the SARS-CoV-2 variant-specific LoD of the pAQ monitor for a 5-minute period of air sampling. The pAQ monitor LoD was 35, 7, 9, and 23 RNA copies / ml for the WA-1, Delta, Beta, and BA-1 strains, respectively. 3 The LoD for viruses in submicron-sized aerosols varies based on the particle size-dependent recovery of the wet cyclone (Figure 16).

[0118] pAQ monitor virus detection sensitivity Different concentrations of test SARS-CoV-2 were prepared by diluting inactivated SARS-CoV-2 stock into PBS solution. Test solutions were aerosolized using a Collison nebulizer in a fume hood (Figure 20). A custom-made wide-mouth glass conical adapter (approximately 4-inch diameter opening) was used to place the Collison aerosol generation port directly in the center of the wet cyclone inlet. Here, we assume that the strong suction force at the wet cyclone inlet ensures that all aerosols generated by the Collison nebulizer enter the cyclone. Along with the viral aerosol, approximately 993 L of clean laboratory air also enters the cyclone. The wet cyclone was filled with 15 ml of PBS solution and aerosolized viral sampling was performed for 5 min. After 5 min, samples were manually removed using a disposable syringe screwed into the bottom of the wet cyclone. The collected samples were manually divided into two, one was analyzed using the biosensor and the other was analyzed by RT-qPCR (within 18 hours of sample collection). After sample collection, the wet cyclone was decontaminated using 70% ethanol. The wet cyclone was washed, rinsed with milli-q water, and air-dried before the next sample collection. Figure 19B shows the performance of the pAQ monitor when sampling laboratory aerosolized inactivated WA-1 and BA-1. The pAQ monitor showed a sensitivity of 77% for WA-1 and 83.3% for BA-1. The virus sensitivity of pAQ is comparable to that of other recently developed rapid biosensors (detection time <10 min) used to detect viruses in saliva, nasal swabs, and exhaled breath condensate samples.

[0119] pAQ Monitor Design for Duct Air Sampling In at least one exemplary embodiment, the device is a duct air sampling instrument (FIG. 12C). In this configuration, the wet cyclone inlet is connected to an air duct of a building ventilation system. Air from the building duct is sampled using a ring blower or vacuum pump connected in series with a pAQ monitor. In this configuration, the pAQ air sampler is divided into three independent modules: (1) the pAQ monitor unit, (2) the hydraulic fluid unit, and (3) the air pump.

[0120] The pAQ monitor unit consists of a wet cyclone sampler, with a front panel touch screen interface that includes data on electrode status (time until replacement, presence of virus, etc.), fluid levels, pump activity, and external variables such as temperature and humidity. Some embodiments further include compactness to reduce power and fluid consumption and facilitate installation in areas where space may be limited. The unit also houses a custom automated biosensor loader. This automated biosensor loader holds 16-48 (or more) pre-calibrated biosensors that are periodically replaced according to sampling frequency.

[0121] The working fluid unit stores the reagents required to operate the pAQ monitor for daily sampling. The modular nature of this unit allows for easy maintenance and refilling of reagents during routine construction maintenance. The size of this unit can be increased or decreased based on the volume of reagents required, the space available, and the ease of handling the reagent bottles when refilling fluids.

[0122] The air pump is housed outside, either outdoors or concealed in a soundproofed area. The modular design allows the air pump to be located away from the pAQ monitor unit, reducing the noise levels to which users are exposed.

[0123] The pAQ Monitor Duct Air Sampling Unit can operate unattended for weeks to a month (or longer) with minimal human assistance.

[0124] The definitions and methods set forth herein are provided to more clearly define the present disclosure and to guide those skilled in the art in the practice of the present disclosure. Unless otherwise noted, terms are to be understood according to conventional usage by those of ordinary skill in the relevant art.

[0125] In some embodiments, numerical values ​​expressing quantities of ingredients, properties such as molecular weights, reaction conditions, and the like, used to describe and claim certain embodiments of the present disclosure are understood to be modified in some cases by the term "about". In some embodiments, the term "about" is used to indicate that the value includes the standard deviation of the mean for the device or method employed to determine the value. In some embodiments, the numerical parameters set forth in this specification and the appended claims are approximations that vary depending on the desired properties sought to be obtained by the particular embodiment. In some embodiments, the numerical parameters are construed in light of the reported number of significant digits and by applying ordinary rounding techniques. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of some embodiments of the present disclosure are approximations, the numerical values ​​set forth in the specific examples are reported as precisely as practicable. The numerical values ​​presented in some embodiments of the present disclosure may contain certain errors necessarily resulting from the standard deviation found in their respective testing measurements. The recitation of ranges of values ​​herein is merely intended to serve as a shorthand method of referring individually to each individual value falling within the range. Unless otherwise indicated herein, each individual value is incorporated herein as if set forth individually herein.

[0126] In some embodiments, the terms "a" and "an" and "the" and similar references used in the context of describing particular embodiments (particularly in the particular context of the claims below) are to be construed to cover both the singular and the plural, unless specifically noted otherwise. In some embodiments, the term "or" as used herein, including the claims, is used to mean "and / or," unless expressly indicated to refer only to alternatives or to alternatives that are mutually exclusive.

[0127] The terms "comprise," "have," and "include" are open-ended linking verbs. One or more forms and tenses of these verbs are also open-ended, such as "comprises," "comprising," "has," "having," "includes," and "including." For example, any method that "comprises," "has," or "includes" one or more steps is not limited to having only those one or more steps, but may also cover other unrecited steps. Similarly, any composition or device that "comprises," "has," or "includes" one or more features is not limited to having only those one or more features, but may also cover other unrecited features.

[0128] All methods described herein may be carried out in any suitable order unless otherwise indicated herein or clearly contradicted by context. Any and all examples provided herein with respect to specific embodiments, or the use of exemplary language (e.g., "such as"), are intended merely to facilitate a better understanding of the disclosure, and do not limit the scope of the disclosure as otherwise claimed. No language in this specification should be construed as indicating a non-claimed element essential to the practice of the disclosure.

[0129] Grouping of alternative elements or embodiments of the disclosure disclosed herein is not to be construed as limiting. Each group member may be referenced and claimed individually or in any combination with other members of the group or other elements found herein. One or more members of a group may be included in or deleted from a group for convenience or reasons of patentability. When such inclusion or deletion is made, the present specification is deemed to include the group as modified to satisfy all Markush group descriptions used in the appended claims.

[0130] To facilitate understanding of the embodiments described herein, certain terms are defined below. Terms defined herein have meanings commonly understood by those skilled in the art to which the present disclosure pertains. Terms such as "a," "an," and "the" are not intended to refer to a singular entity only, but rather include a general class of which a particular example may be used for illustration. Terms herein are used to describe specific embodiments of the present disclosure, but their use does not define the scope of the present disclosure, except as outlined in the claims.

[0131] All compositions and / or methods disclosed and claimed herein can be made and / or carried out without undue experimentation in light of the present disclosure. Although the compositions and methods of the present disclosure are described in terms of the embodiments contained herein, it will be apparent to those skilled in the art that variations may be applied in the compositions and / or methods described herein, and in the steps or sequence of steps of the methods, without departing from the concept, spirit and scope of the present disclosure. All such similar substitutes and modifications apparent to those skilled in the art are deemed to be within the spirit, scope and concept of the present disclosure as defined by the appended claims.

[0132] This specification uses examples to disclose the disclosure, including the best mode, and to enable those skilled in the art to practice the disclosure, including making and using any devices or systems, and performing the incorporated methods. The patentable scope of the disclosure is defined by the claims, but may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal words of the claims, or if they include equivalent structural elements that do not differ substantially from the literal words of the claims.

Claims

1. 1. An airborne particle detection device for analyzing environmental air samples and detecting airborne pathogens, comprising: an analytical vial; and Biosensor Electrodes 13. An apparatus comprising:

2. 13. The device of claim 1 configured to be used to simultaneously detect multiple pathogens in a single test.

3. 3. The apparatus of claim 2, wherein the plurality of pathogens is a combination of pathogens, each of the pathogens being selected from the group consisting of a virus, a bacterium, a parasite, a fungus, a mold, a plurality of viruses, a plurality of bacteria, a plurality of viral species or strains, a plurality of bacterial species or strains, a plurality of parasitic species or strains, a plurality of fungal species or strains, and a plurality of mold species or strains.

4. 13. The device of claim 1, used to test for multiple variants of a pathogen from a single test.

5. 5. The device of claim 4, wherein the multiple mutants of a pathogen include delta and omicron mutants of SARS-CoV-2.

6. 13. The device of claim 1 configured for use in multiple testing.

7. 7. The device of claim 6, wherein multiple pathogens are detected simultaneously in the multiplex test.

8. 1. A method for detecting airborne pathogens, comprising: transporting a liquid sample from an external sampling device, which may be a hydrocyclone particulate liquid sampler (PILS), to an analysis vial of the airborne particles detection device; adding a working fluid to the analysis vial of the airborne particle detection device; Detecting at least one pathogen; Replenishing the external sampling device with sample liquid; and Discharging the analytical sample from said analytical vial into a waste reservoir of said airborne particle detection device. A method comprising:

9. 10. The method of claim 8, wherein detecting at least one pathogen comprises simultaneously detecting multiple pathogens in a single test.

10. 10. The method of claim 9, wherein the plurality of pathogens is a combination of pathogens, each of the pathogens being selected from the group consisting of a virus, a bacterium, a parasite, a fungus, a mold, a plurality of viruses, a plurality of bacteria, a plurality of viral species or strains, a plurality of bacterial species or strains, a plurality of parasitic species or strains, a plurality of fungal species or strains, and a plurality of mold species or strains.

11. 10. The method of claim 8, wherein detecting at least one pathogen comprises detecting multiple variants of the pathogen from a single test.

12. 12. The method of claim 11, wherein the multiple mutants of a pathogen include delta and omicron mutants of SARS-CoV-2.

13. 10. The method of claim 8, wherein detecting at least one pathogen comprises multiplex detection, wherein multiple pathogens are detected simultaneously.

14. 1. A system for detecting airborne pathogens, comprising: An airborne particle detection device; and An external sampling device which may be a hydrocyclone particle liquid sampler (PILS) Including, the system.

15. 15. The system of claim 14, used to simultaneously detect multiple pathogens in a single test.

16. 16. The system of claim 15, wherein the plurality of pathogens is a combination of pathogens, each of the pathogens being selected from the group consisting of a virus, a bacterium, a parasite, a fungus, a mold, a plurality of viruses, a plurality of bacteria, a plurality of viral species or strains, a plurality of bacterial species or strains, a plurality of parasitic species or strains, a plurality of fungal species or strains, and a plurality of mold species or strains.

17. 15. The system of claim 14, used to test for multiple variants of a pathogen from a single test.

18. 18. The system of claim 17, wherein the multiple variants of a pathogen include delta and omicron variants of SARS-CoV-2.

19. 15. The system of claim 14 configured for use in multiple testing.

20. 20. The system of claim 19, wherein multiple pathogens are detected simultaneously in the multiplex test.

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