Metagenomic Analysis of the Outdoor Dust Microbiomes: A Case Study from Abu Dhabi, UAE

Outdoor dust covers a shattered range of microbial agents from land over transportation, human microbial flora, which includes pathogen and commensals, and airborne from the environment. Dust aerosols are rich in bacterial communities that have a major impact on human health and living environments. In this study, outdoor samples from roadside barricades, safety walls, and fences (18 samples) were collected from Abu Dhabi, UAE and bacterial diversity was assessed through a 16S rRNA amplicon next generation sequencing approach. Clean data from HiSeq produced 1,099,892 total reads pairs for 18 samples. For all samples, taxonomic classifications were assigned to the OTUs (operational taxonomic units) representative sequence using the Ribosomal Database Project database. Analysis such as alpha diversity, beta diversity, differential species analysis, and species relative abundance were performed in the clustering of samples and a functional profile heat map was obtained from the OTUs by using bioinformatics tools. A total of 2814 OTUs were identified from those samples with a coverage of more than 99%. In the phylum, all 18 samples had most of the bacterial groups such as Actinobacteria, Proteobacteria, Firmicutes, and Bacteroidetes. Twelve samples had Propionibacteria acnes and were mainly found in RD16 and RD3. Major bacteria species such as Propionibacteria acnes, Bacillus persicus, and Staphylococcus captis were found in all samples. Most of the samples had Streptococcus mitis, Staphylococcus capitis. and Nafulsella turpanensis and Enhydrobacter aerosaccus was part of the normal microbes of the skin. Salinimicrobium sp., Bacillus alkalisediminis, and Bacillus persicus are halophilic bacteria found in sediments. The heat map clustered the samples and species in vertical and horizontal classification, which represents the relationship between the samples and bacterial diversity. The heat map for the functional profile had high properties of amino acids, carbohydrate, and cofactor and vitamin metabolisms of all bacterial species from all samples. Taken together, our analyses are very relevant from the perspective of out-door air quality, airborne diseases, and epidemics, with broader implications for health safety and monitoring

Multipollutant Abatement through Visible Photocatalytic System

Water pollution damages the aquatic environment due to the presence of organic contaminants, which in turn is distressing to the ecosystem. Photocatalytic activity is a greener and promising method to degrade these organic contaminants. In this research, we present the degradation of diverse water pollutants through zinc/iron oxide nanoparticles serving as photocatalysts. The photocatalyst was studied for its efficiency to photodegrade congo red, brilliant green and para nitro phenol. Moreover, it also presented an antibacterial activity against the bacterium E. coli. Photocatalyst was characterized via X-ray diffraction, scanning electron microscopy-energy dispersive X-ray spectroscopy, and fourier-transform infrared spectroscopy. Tauc plot was used to measure the optical band gap (1.84 eV). The effect of various parameters such as catalyst dose, contact time, dye dose/concentration and pH were also investigated to determine the optimum point of maximum degradation through response surface methodology. A face-centered composite design was used, and a quadratic model was followed by congo red, brilliant green dyes and para nitrophenol. The maximum photodegradation efficiencies were 99%, 94.3%, and 78.5% for congo red, brilliant green and phenol, respectively. Quantum yield for congo red, brilliant green and para-nitrophenol were 9.62 × 10−8, 1.17 × 10−7 and 4.11 × 10−7 molecules/photons, while the reaction rates were 27.1 µmolg−1h−1, 29.61 µmolg−1h−1 and 231 µmolg−1h−1, respectively

Metagenomic Analysis of the Outdoor Dust Microbiomes: A Case Study from Abu Dhabi, UAE

Outdoor dust covers a shattered range of microbial agents from land over transportation, human microbial flora, which includes pathogen and commensals, and airborne from the environment. Dust aerosols are rich in bacterial communities that have a major impact on human health and living environments. In this study, outdoor samples from roadside barricades, safety walls, and fences (18 samples) were collected from Abu Dhabi, UAE and bacterial diversity was assessed through a 16S rRNA amplicon next generation sequencing approach. Clean data from HiSeq produced 1,099,892 total reads pairs for 18 samples. For all samples, taxonomic classifications were assigned to the OTUs (operational taxonomic units) representative sequence using the Ribosomal Database Project database. Analysis such as alpha diversity, beta diversity, differential species analysis, and species relative abundance were performed in the clustering of samples and a functional profile heat map was obtained from the OTUs by using bioinformatics tools. A total of 2814 OTUs were identified from those samples with a coverage of more than 99%. In the phylum, all 18 samples had most of the bacterial groups such as Actinobacteria, Proteobacteria, Firmicutes, and Bacteroidetes. Twelve samples had Propionibacteria acnes and were mainly found in RD16 and RD3. Major bacteria species such as Propionibacteria acnes, Bacillus persicus, and Staphylococcus captis were found in all samples. Most of the samples had Streptococcus mitis, Staphylococcus capitis. and Nafulsella turpanensis and Enhydrobacter aerosaccus was part of the normal microbes of the skin. Salinimicrobium sp., Bacillus alkalisediminis, and Bacillus persicus are halophilic bacteria found in sediments. The heat map clustered the samples and species in vertical and horizontal classification, which represents the relationship between the samples and bacterial diversity. The heat map for the functional profile had high properties of amino acids, carbohydrate, and cofactor and vitamin metabolisms of all bacterial species from all samples. Taken together, our analyses are very relevant from the perspective of out-door air quality, airborne diseases, and epidemics, with broader implications for health safety and monitoring

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use

Characteristics and outcomes of an international cohort of 600 000 hospitalized patients with COVID-19

Background: We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world's largest international, standardized data sets concerning hospitalized patients. Methods: The data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admission to an intensive care unit (ICU) and invasive mechanical ventilation (IMV). Results: Data were available for 689 572 patients with laboratory-confirmed (91.1%) or clinically diagnosed (8.9%) SARS-CoV-2 infection from 52 countries. Age [adjusted hazard ratio per 10 years 1.49 (95% CI 1.48, 1.49)] and male sex [1.23 (1.21, 1.24)] were associated with a higher risk of death. Rates of admission to an ICU and use of IMV increased with age up to age 60 years then dropped. Symptoms, co-morbidities and treatments varied by age and had varied associations with clinical outcomes. The case-fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients and was on average 21.5%. Conclusions: Age was the strongest determinant of risk of death, with a ∼30-fold difference between the oldest and youngest groups; each of the co-morbidities included was associated with up to an almost 2-fold increase in risk. Smoking and obesity were also associated with a higher risk of death. The size of our international database and the standardized data collection method make this study a comprehensive international description of COVID-19 clinical features. Our findings may inform strategies that involve prioritization of patients hospitalized with COVID-19 who have a higher risk of death

The value of open-source clinical science in pandemic response: lessons from ISARIC

International audienc