1
|
An T, Liang Z, Chen Z, Li G. Recent progress in online detection methods of bioaerosols. FUNDAMENTAL RESEARCH 2024; 4:442-454. [PMID: 38933213 PMCID: PMC10239662 DOI: 10.1016/j.fmre.2023.05.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 04/03/2023] [Accepted: 05/03/2023] [Indexed: 10/29/2023] Open
Abstract
The aerosol transmission of coronavirus disease in 2019, along with the spread of other respiratory diseases, caused significant loss of life and property; it impressed upon us the importance of real-time bioaerosol detection. The complexity, diversity, and large spatiotemporal variability of bioaerosols and their external/internal mixing with abiotic components pose challenges for effective online bioaerosol monitoring. Traditional methods focus on directly capturing bioaerosols before subsequent time-consuming laboratory analysis such as culture-based methods, preventing the high-resolution time-based characteristics necessary for an online approach. Through a comprehensive literature assessment, this review highlights and discusses the most commonly used real-time bioaerosol monitoring techniques and the associated commercially available monitors. Methods applied in online bioaerosol monitoring, including adenosine triphosphate bioluminescence, laser/light-induced fluorescence spectroscopy, Raman spectroscopy, and bioaerosol mass spectrometry are summarized. The working principles, characteristics, sensitivities, and efficiencies of these real-time detection methods are compared to understand their responses to known particle types and to contrast their differences. Approaches developed to analyze the substantial data sets obtained by these instruments and to overcome the limitations of current real-time bioaerosol monitoring technologies are also introduced. Finally, an outlook is proposed for future instrumentation indicating a need for highly revolutionized bioaerosol detection technologies.
Collapse
Affiliation(s)
- Taicheng An
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, Institute of Environmental Health and Pollution control, Guangdong University of Technology, Guangzhou 510006, China
- Guangzhou Key Laboratory of Environmental Catalysis and Pollution Control, Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, School of Environmental Science and Engineering, Institute of Environmental Health and Pollution Control, Guangdong University of Technology, Guangzhou 510006, China
| | - Zhishu Liang
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, Institute of Environmental Health and Pollution control, Guangdong University of Technology, Guangzhou 510006, China
- Guangzhou Key Laboratory of Environmental Catalysis and Pollution Control, Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, School of Environmental Science and Engineering, Institute of Environmental Health and Pollution Control, Guangdong University of Technology, Guangzhou 510006, China
| | - Zhen Chen
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, Institute of Environmental Health and Pollution control, Guangdong University of Technology, Guangzhou 510006, China
| | - Guiying Li
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, Institute of Environmental Health and Pollution control, Guangdong University of Technology, Guangzhou 510006, China
- Guangzhou Key Laboratory of Environmental Catalysis and Pollution Control, Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, School of Environmental Science and Engineering, Institute of Environmental Health and Pollution Control, Guangdong University of Technology, Guangzhou 510006, China
| |
Collapse
|
2
|
Mohammad N, Huguenin A, Lefebvre A, Menvielle L, Toubas D, Ranque S, Villena I, Tannier X, Normand AC, Piarroux R. Nosocomial transmission of Aspergillus flavus in a neonatal intensive care unit: Long-term persistence in environment and interest of MALDI-ToF mass-spectrometry coupled with convolutional neural network for rapid clone recognition. Med Mycol 2024; 62:myad136. [PMID: 38142226 DOI: 10.1093/mmy/myad136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 11/28/2023] [Accepted: 12/21/2023] [Indexed: 12/25/2023] Open
Abstract
Aspergillosis of the newborn remains a rare but severe disease. We report four cases of primary cutaneous Aspergillus flavus infections in premature newborns linked to incubators contamination by putative clonal strains. Our objective was to evaluate the ability of matrix-assisted laser desorption/ionisation time of flight (MALDI-TOF) coupled to convolutional neural network (CNN) for clone recognition in a context where only a very small number of strains are available for machine learning. Clinical and environmental A. flavus isolates (n = 64) were studied, 15 were epidemiologically related to the four cases. All strains were typed using microsatellite length polymorphism. We found a common genotype for 9/15 related strains. The isolates of this common genotype were selected to obtain a training dataset (6 clonal isolates/25 non-clonal) and a test dataset (3 clonal isolates/31 non-clonal), and spectra were analysed with a simple CNN model. On the test dataset using CNN model, all 31 non-clonal isolates were correctly classified, 2/3 clonal isolates were unambiguously correctly classified, whereas the third strain was undetermined (i.e., the CNN model was unable to discriminate between GT8 and non-GT8). Clonal strains of A. flavus have persisted in the neonatal intensive care unit for several years. Indeed, two strains of A. flavus isolated from incubators in September 2007 are identical to the strain responsible for the second case that occurred 3 years later. MALDI-TOF is a promising tool for detecting clonal isolates of A. flavus using CNN even with a limited training set for limited cost and handling time.
Collapse
Affiliation(s)
- Noshine Mohammad
- Sorbonne Université, INSERM, Institut Pierre-Louis d'Epidémiologie et de Santé Publique, AP-HP, Paris, France
- Groupe Hospitalier Pitié-Salpêtrière, Service de Parasitologie-Mycologie, Paris, France
| | - Antoine Huguenin
- Laboratoire de Parasitologie-Mycologie, Pôle de Biologie et de Pathologie, CHU de Reims, Reims, France
- Université de Reims Champagne Ardenne, ESCAPE EA7510, Reims, France
| | | | - Laura Menvielle
- CHU de Reims, Hôpital Américain, Service de réanimation néonatale, 45 rue Cognaq Jay, Reims, France
| | - Dominique Toubas
- Laboratoire de Parasitologie-Mycologie, Pôle de Biologie et de Pathologie, CHU de Reims, Reims, France
- Université de Reims Champagne Ardenne, ESCAPE EA7510, Reims, France
- Equipe Opérationnelle d'Hygiène, CHU de Reims, France
- CHU de Reims, Hôpital Américain, Service de réanimation néonatale, 45 rue Cognaq Jay, Reims, France
- BioSpecT (Translational BioSpectroscopy) EA 7506, SFR Santé, Université de Reims Champagne-Ardenne, Reims, France
| | - Stéphane Ranque
- IHU-Méditerranée Infection, Marseille, France
- Aix-Marseille Université, AP-HM, IRD, SSA, VITROME, Marseille, France
| | - Isabelle Villena
- Laboratoire de Parasitologie-Mycologie, Pôle de Biologie et de Pathologie, CHU de Reims, Reims, France
- Université de Reims Champagne Ardenne, ESCAPE EA7510, Reims, France
| | - Xavier Tannier
- Sorbonne Université, INSERM, Université Sorbonne Paris Nord, Laboratoire d'Informatique Médicale et d'Ingénierie des connaissances en e-Santé, LIMICS, Paris, France
| | - Anne-Cécile Normand
- Groupe Hospitalier Pitié-Salpêtrière, Service de Parasitologie-Mycologie, Paris, France
| | - Renaud Piarroux
- Sorbonne Université, INSERM, Institut Pierre-Louis d'Epidémiologie et de Santé Publique, AP-HP, Paris, France
- Groupe Hospitalier Pitié-Salpêtrière, Service de Parasitologie-Mycologie, Paris, France
| |
Collapse
|
3
|
Tsioutis C, Karageorgos SA. Infection Prevention and Control: Practical and Educational Advances. Trop Med Infect Dis 2022; 7:tropicalmed7080148. [PMID: 35893656 PMCID: PMC9330796 DOI: 10.3390/tropicalmed7080148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 07/25/2022] [Indexed: 12/10/2022] Open
Affiliation(s)
- Constantinos Tsioutis
- School of Medicine, European University Cyprus, Egkomi 2404, Cyprus;
- Correspondence:
| | - Spyridon A. Karageorgos
- School of Medicine, European University Cyprus, Egkomi 2404, Cyprus;
- First Department of Pediatrics, Aghia Sophia Children’s Hospital, National and Kapodistrian University of Athens, 11527 Athens, Greece
| |
Collapse
|