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Chibwe K, Sundararaju S, Zhang L, Tsui C, Tang P, Ling F. Intra-hospital microbiome variability is driven by accessibility and clinical activities. Microbiol Spectr 2024; 12:e0029624. [PMID: 38940596 PMCID: PMC11302010 DOI: 10.1128/spectrum.00296-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Accepted: 05/30/2024] [Indexed: 06/29/2024] Open
Abstract
The hospital environmental microbiome, which can affect patients' and healthcare workers' health, is highly variable and the drivers of this variability are not well understood. In this study, we collected 37 surface samples from the neonatal intensive care unit (NICU) in an inpatient hospital before and after the operation began. Additionally, healthcare workers collected 160 surface samples from five additional areas of the hospital. All samples were analyzed using 16S rRNA gene amplicon sequencing, and the samples collected by healthcare workers were cultured. The NICU samples exhibited similar alpha and beta diversities before and after opening, which indicated that the microbiome there was stable over time. Conversely, the diversities of samples taken after opening varied widely by area. Principal coordinate analysis (PCoA) showed the samples clustered into two distinct groups: high alpha diversity [the pediatric intensive care unit (PICU), pathology lab, and microbiology lab] and low alpha diversity [the NICU, pediatric surgery ward, and infection prevention and control (IPAC) office]. Least absolute shrinkage and selection operator (LASSO) classification models identified 156 informative amplicon sequence variants (ASVs) for predicting the sample's area of origin. The testing accuracy ranged from 86.37% to 100%, which outperformed linear and radial support vector machine (SVM) and random forest models. ASVs of genera that contain emerging pathogens were identified in these models. Culture experiments had identified viable species among the samples, including potential antibiotic-resistant bacteria. Though area type differences were not noted in the culture data, the prevalences and relative abundances of genera detected positively correlated with 16S sequencing data. This study brings to light the microbial community temporal and spatial variation within the hospital and the importance of pathogenic and commensal bacteria to understanding dispersal patterns for infection control. IMPORTANCE We sampled surface samples from a newly built inpatient hospital in multiple areas, including areas accessed by only healthcare workers. Our analysis of the neonatal intensive care unit (NICU) showed that the microbiome was stable before and after the operation began, possibly due to access restrictions. Of the high-touch samples taken after opening, areas with high diversity had more potential external seeds (long-term patients and clinical samples), and areas with low diversity and had fewer (short-term or newborn patients). Classification models performed at high accuracy and identified biomarkers that could be used for more targeted surveillance and infection control. Though culturing data yielded viability and antibiotic-resistance information, it disproportionately detected the presence of genera relative to 16S data. This difference reinforces the utility of 16S sequencing in profiling hospital microbiomes. By examining the microbiome over time and in multiple areas, we identified potential drivers of the microbial variation within a hospital.
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Affiliation(s)
- Kaseba Chibwe
- Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | | | - Lin Zhang
- Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Clement Tsui
- Department of Pathology, Sidra Medicine, Doha, Qatar
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine-Qatar, Doha, Qatar
- Faculty of Medicine, University of British Columbia, Vancouver, Canada
- Infectious Diseases Research Laboratory, National Centre for Infectious Diseases, Singapore
| | - Patrick Tang
- Department of Pathology, Sidra Medicine, Doha, Qatar
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine-Qatar, Doha, Qatar
| | - Fangqiong Ling
- Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
- Division of Biological and Biomedical Sciences, Washington University in St. Louis, St. Louis, Missouri, USA
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
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Bellato M, Cappellato M, Longhin F, Del Vecchio C, Brancaccio G, Cattelan AM, Brun P, Salaris C, Castagliuolo I, Di Camillo B. Uncover a microbiota signature of upper respiratory tract in patients with SARS-CoV-2 + . Sci Rep 2023; 13:16867. [PMID: 37803040 PMCID: PMC10558486 DOI: 10.1038/s41598-023-43040-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 09/18/2023] [Indexed: 10/08/2023] Open
Abstract
The outbreak of Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, forced us to face a pandemic with unprecedented social, economic, and public health consequences. Several nations have launched campaigns to immunize millions of people using various vaccines to prevent infections. Meanwhile, therapeutic approaches and discoveries continuously arise; however, identifying infected patients that are going to experience the more severe outcomes of COVID-19 is still a major need, to focus therapeutic efforts, reducing hospitalization and mitigating drug adverse effects. Microbial communities colonizing the respiratory tract exert significant effects on host immune responses, influencing the susceptibility to infectious agents. Through 16S rDNAseq we characterized the upper airways' microbiota of 192 subjects with nasopharyngeal swab positive for SARS-CoV-2. Patients were divided into groups based on the presence of symptoms, pneumonia severity, and need for oxygen therapy or intubation. Indeed, unlike most of the literature, our study focuses on identifying microbial signatures predictive of disease progression rather than on the probability of infection itself, for which a consensus is lacking. Diversity, differential abundance, and network analysis at different taxonomic levels were synergistically adopted, in a robust bioinformatic pipeline, highlighting novel possible taxa correlated with patients' disease progression to intubation.
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Affiliation(s)
- Massimo Bellato
- Department of Information Engineering, University of Padova, 35131, Padova, Italy
| | - Marco Cappellato
- Department of Information Engineering, University of Padova, 35131, Padova, Italy
| | - Francesca Longhin
- Department of Information Engineering, University of Padova, 35131, Padova, Italy
| | - Claudia Del Vecchio
- Department of Molecular Medicine, University of Padova, 35121, Padova, Italy
| | - Giuseppina Brancaccio
- Department of Molecular Medicine, University of Padova, 35121, Padova, Italy
- Infectious Diseases Unit, University Hospital Padova, 35128, Padova, Italy
| | - Anna Maria Cattelan
- Department of Molecular Medicine, University of Padova, 35121, Padova, Italy
- Infectious Diseases Unit, University Hospital Padova, 35128, Padova, Italy
| | - Paola Brun
- Department of Molecular Medicine, University of Padova, 35121, Padova, Italy
| | - Claudio Salaris
- Department of Molecular Medicine, University of Padova, 35121, Padova, Italy
| | - Ignazio Castagliuolo
- Department of Molecular Medicine, University of Padova, 35121, Padova, Italy
- Microbiology and Virology Unit, University Hospital Padova, 35121, Padova, Italy
| | - Barbara Di Camillo
- Department of Information Engineering, University of Padova, 35131, Padova, Italy.
- Department of Comparative Biomedicine and Food Science, University of Padova, 35020, Legnaro (PD), Italy.
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Siew SW, Musa SM, Sabri N'A, Farida Asras MF, Ahmad HF. Evaluation of pre-treated healthcare wastes during COVID-19 pandemic reveals pathogenic microbiota, antibiotics residues, and antibiotic resistance genes against beta-lactams. ENVIRONMENTAL RESEARCH 2023; 219:115139. [PMID: 36565841 PMCID: PMC9771581 DOI: 10.1016/j.envres.2022.115139] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 11/25/2022] [Accepted: 12/20/2022] [Indexed: 06/17/2023]
Abstract
The disposal of healthcare waste without prior elimination of pathogens and hazardous contaminants has negative effects on the environment and public health. This study aimed to profile the complete microbial community and correlate it with the antibiotic compounds identified in microwave pre-treated healthcare wastes collected from three different waste operators in Peninsular Malaysia. The bacterial and fungal compositions were determined via amplicon sequencing by targeting the full-length 16S rRNA gene and partial 18S with full-length ITS1-ITS2 regions, respectively. The antibiotic compounds were characterized using high-throughput spectrometry. There was significant variation in bacterial and fungal composition in three groups of samples, with alpha- (p-value = 0.04) and beta-diversity (p-values <0.006 and < 0.002), respectively. FC samples were found to acquire more pathogenic microorganisms than FA and FV samples. Paenibacillus and unclassified Bacilli genera were shared among three groups of samples, meanwhile, antibiotic-resistant bacteria Proteus mirabilis, Enterococcus faecium, and Enterococcus faecalis were found in modest quantities. A total of 19 antibiotic compounds were discovered and linked with the microbial abundance detected in the healthcare waste samples. The principal component analysis demonstrated a positive antibiotic-bacteria correlation for genera Pseudomonas, Aerococcus, Comamonas, and Vagococcus, while the other bacteria were negatively linked with antibiotics. Nevertheless, deep bioinformatic analysis confirmed the presence of blaTEM-1 and penP which are associated with the production of class A beta-lactamase and beta-lactam resistance pathways. Microorganisms and contaminants, which serve as putative indicators in healthcare waste treatment evaluation revealed the ineffectiveness of microbial inactivation using the microwave sterilization method. Our findings suggested that the occurrence of clinically relevant microorganisms, antibiotic contaminants, and associated antibiotic resistance genes (ARGs) represent environmental and human health hazards when released into landfills via ARGs transmission.
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Affiliation(s)
- Shing Wei Siew
- Faculty of Industrial Sciences and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300, Gambang, Pahang, Malaysia.
| | - Siti Munirah Musa
- Faculty of Industrial Sciences and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300, Gambang, Pahang, Malaysia.
| | - Nurul 'Azyyati Sabri
- Faculty of Industrial Sciences and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300, Gambang, Pahang, Malaysia; Group of Environment, Microbiology and Bioprocessing (GERMS), Lebuhraya Tun Razak, 26300, Gambang, Pahang, Malaysia.
| | - Mohd Fazli Farida Asras
- Faculty of Industrial Sciences and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300, Gambang, Pahang, Malaysia; Group of Environment, Microbiology and Bioprocessing (GERMS), Lebuhraya Tun Razak, 26300, Gambang, Pahang, Malaysia.
| | - Hajar Fauzan Ahmad
- Faculty of Industrial Sciences and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300, Gambang, Pahang, Malaysia; Group of Environment, Microbiology and Bioprocessing (GERMS), Lebuhraya Tun Razak, 26300, Gambang, Pahang, Malaysia.
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Perrone MR, Romano S, De Maria G, Tundo P, Bruno AR, Tagliaferro L, Maffia M, Fragola M. Simultaneous monitoring of SARS-CoV-2 and bacterial profiles from the air of hospital environments with COVID-19-affected patients. AEROBIOLOGIA 2022; 38:391-412. [PMID: 36097443 PMCID: PMC9453715 DOI: 10.1007/s10453-022-09754-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 08/01/2022] [Indexed: 06/15/2023]
Abstract
UNLABELLED The SARS-CoV-2 presence and the bacterial community profile in air samples collected at the Intensive Care Unit (ICU) of the Operational Unit of Infectious Diseases of Santa Caterina Novella Hospital in Galatina (Lecce, Italy) have been evaluated in this study. Air samplings were performed in different rooms of the ICU ward with and without COVID-19 patients. No sample was found positive to SARS-CoV-2, according to Allplex 2019-nCoV Assay. The airborne bacterial community profiles determined by the 16S rRNA gene metabarcoding approach up to the species level were characterized by richness and biodiversity indices, Spearman correlation coefficients, and Principal Coordinate Analysis. Pathogenic and non-pathogenic bacterial species, also detected in outdoor air samples, were found in all collected indoor samples. Staphylococcus pettenkoferi, Corynebacterium tuberculostearicum, and others coagulase-negative staphylococci, detected at high relative abundances in all the patients' rooms, were the most abundant pathogenic species. The highest mean relative abundance of S. pettenkoferi and C. tuberculostearicum suggested that they were likely the main pathogens of COVID-19 patients at the ICU ward of this study. The identification of nosocomial pathogens representing potential patients' risks in ICU COVID-19 rooms and the still controversial airborne transmission of the SARS-CoV-2 are the main contributions of this study. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s10453-022-09754-7.
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Affiliation(s)
- Maria Rita Perrone
- Department of Mathematics and Physics, University of Salento, 73100 Lecce, Italy
| | - Salvatore Romano
- Department of Mathematics and Physics, University of Salento, 73100 Lecce, Italy
| | - Giuseppe De Maria
- Presidio Ospedaliero Santa Caterina Novella, Azienda Sanitaria Locale Lecce, 73013 Galatina, Lecce, Italy
| | - Paolo Tundo
- Presidio Ospedaliero Santa Caterina Novella, Azienda Sanitaria Locale Lecce, 73013 Galatina, Lecce, Italy
| | - Anna Rita Bruno
- Presidio Ospedaliero Santa Caterina Novella, Azienda Sanitaria Locale Lecce, 73013 Galatina, Lecce, Italy
| | - Luigi Tagliaferro
- Presidio Ospedaliero Santa Caterina Novella, Azienda Sanitaria Locale Lecce, 73013 Galatina, Lecce, Italy
| | - Michele Maffia
- Department of Biological and Environmental Sciences and Technologies, University of Salento, 73100 Lecce, Italy
| | - Mattia Fragola
- Department of Mathematics and Physics, University of Salento, 73100 Lecce, Italy
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Perrone MR, Romano S, De Maria G, Tundo P, Bruno AR, Tagliaferro L, Maffia M, Fragola M. Compositional Data Analysis of 16S rRNA Gene Sequencing Results from Hospital Airborne Microbiome Samples. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:10107. [PMID: 36011742 PMCID: PMC9408509 DOI: 10.3390/ijerph191610107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 08/05/2022] [Accepted: 08/06/2022] [Indexed: 06/15/2023]
Abstract
The compositional analysis of 16S rRNA gene sequencing datasets is applied to characterize the bacterial structure of airborne samples collected in different locations of a hospital infection disease department hosting COVID-19 patients, as well as to investigate the relationships among bacterial taxa at the genus and species level. The exploration of the centered log-ratio transformed data by the principal component analysis via the singular value decomposition has shown that the collected samples segregated with an observable separation depending on the monitoring location. More specifically, two main sample clusters were identified with regards to bacterial genera (species), consisting of samples mostly collected in rooms with and without COVID-19 patients, respectively. Human pathogenic genera (species) associated with nosocomial infections were mostly found in samples from areas hosting patients, while non-pathogenic genera (species) mainly isolated from soil were detected in the other samples. Propionibacterium acnes, Staphylococcus pettenkoferi, Corynebacterium tuberculostearicum, and jeikeium were the main pathogenic species detected in COVID-19 patients' rooms. Samples from these locations were on average characterized by smaller richness/evenness and diversity than the other ones, both at the genus and species level. Finally, the ρ metrics revealed that pairwise positive associations occurred either between pathogenic or non-pathogenic taxa.
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Affiliation(s)
- Maria Rita Perrone
- Department of Mathematics and Physics, University of Salento, 73100 Lecce, Italy
| | - Salvatore Romano
- Department of Mathematics and Physics, University of Salento, 73100 Lecce, Italy
| | - Giuseppe De Maria
- Presidio Ospedaliero Santa Caterina Novella, Azienda Sanitaria Locale Lecce, 73013 Galatina, Italy
| | - Paolo Tundo
- Presidio Ospedaliero Santa Caterina Novella, Azienda Sanitaria Locale Lecce, 73013 Galatina, Italy
| | - Anna Rita Bruno
- Presidio Ospedaliero Santa Caterina Novella, Azienda Sanitaria Locale Lecce, 73013 Galatina, Italy
| | - Luigi Tagliaferro
- Presidio Ospedaliero Santa Caterina Novella, Azienda Sanitaria Locale Lecce, 73013 Galatina, Italy
| | - Michele Maffia
- Department of Biological and Environmental Sciences and Technologies, University of Salento, 73100 Lecce, Italy
| | - Mattia Fragola
- Department of Mathematics and Physics, University of Salento, 73100 Lecce, Italy
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Su B, Zhang T, Yan L, Huang C, Cheng X, Cai C, Cui D. Online Medical Teaching in China During the COVID-19 Pandemic: Tools, Modalities, and Challenges. Front Public Health 2021; 9:797694. [PMID: 34988057 PMCID: PMC8720748 DOI: 10.3389/fpubh.2021.797694] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 11/29/2021] [Indexed: 12/23/2022] Open
Abstract
Background: The novel coronavirus disease 2019 (COVID-19) pandemic has tested the ability of universities to provide a high-quality, safe educational experience for students due to campuses shutting down. As a result, online learning could shift from a traditional classroom teaching mode and make education accessible to students. Previous studies have used individual online teaching cases to exploit a variety of online learning tools to ensure the continuation of medical education during this difficult time in China. However, for the first time, we have conducted a systematic review of local online teaching approaches, existing challenges, and potential solutions. Purpose: We present the issues and experience of conducting online medical teaching practices in China with the aim of communicating them to our peers in other countries or regions when examining the transition to e-learning during the COVID-19 pandemic and beyond. Methods: We searched the keywords below from public databases and reviewed relevant publications reporting on medical online teaching in China during the COVID-19 pandemic to analyze and summarize the online tools, modalities, and challenges. Results: We listed common online teaching tools and described a variety of online teaching modalities, as well as possible challenges. We also discussed potential solutions for those challenges, as well as the impact of the transition to online teaching on traditional education. Conclusion: By investigating local online medical teaching in China, we present useful tools and modalities that have been successfully exploited in education during the difficult time of COVID-19, although some challenges remain. The exploration of the transition to online teaching or learning will likely continue to have a profound impact on traditional classroom teaching.
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Affiliation(s)
- Bin Su
- Beijing Key Laboratory for HIV/AIDS Research, Sino-French Joint Laboratory for Research on Humoral Immune Response to HIV Infection, Clinical and Research Center for Infectious Diseases, Beijing Youan Hospital, Capital Medical University, Beijing, China
| | - Tong Zhang
- Beijing Key Laboratory for HIV/AIDS Research, Sino-French Joint Laboratory for Research on Humoral Immune Response to HIV Infection, Clinical and Research Center for Infectious Diseases, Beijing Youan Hospital, Capital Medical University, Beijing, China
| | - Li Yan
- Department of Education, Beijing Youan Hospital, Capital Medical University, Beijing, China
| | - Chaoyang Huang
- Department of Education, Beijing Youan Hospital, Capital Medical University, Beijing, China
| | - Xiangpu Cheng
- Department of Education, Beijing Youan Hospital, Capital Medical University, Beijing, China
| | - Chao Cai
- Department of Education, Beijing Youan Hospital, Capital Medical University, Beijing, China
| | - Dan Cui
- Department of Education, Beijing Youan Hospital, Capital Medical University, Beijing, China
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