Coinfections in patients hospitalized with COVID-19: a descriptive study from the United Arab Emirates

Purpose: Microbial coinfections in COVID-19 patients carry a risk of poor outcomes. This study aimed to characterize the clinical and microbiological profiles of coinfections in patients with COVID-19. Methods: A retrospective review of the clinical and laboratory records of COVID-19 patients with laboratory-confirmed infections with bacteria, fungi, and viruses was conducted. Only adult COVID-19 patients hospitalized at participating health-care facilities between February 1 and July 31, 2020 were included. Data were collected from the centralized electronic system of Dubai Health Authority hospitals and Sheikh Khalifa General Hospital Umm Al Quwain. Results: Of 29,802 patients hospitalized with COVID-19, 392 (1.3%) had laboratory-confirmed coinfections. The mean age of patients with coinfections was 49.3± 12.5 years, and a majority were male (n=330 of 392, 84.2%). Mean interval to commencement of empirical antibiotics was 1.2± 3.6) days postadmission, with ceftriaxone, azithromycin, and piperacillin–tazobactam the most commonly used. Median interval between admission and first positive culture (mostly from blood, endotracheal aspirates, and urine specimens) was 15 (IQR 8– 25) days. Pseudomonas aeruginosa, Klebsiella pneumoniae, and Escherichia coli were predominant in first positive cultures, with increased occurrence of Stenotrophomonas maltophilia, methicillin-resistant Staphylococcus aureus, Acinetobacter baumannii, Candida auris, and Candida parapsilosis in subsequent cultures. The top three Gram-positive organisms were Staphylococcus epidermidis, Enterococcus faecalis, and Staphylococcus aureus. There was variability in levels of sensitivity to antibiotics and isolates harboring mecA, ESBL, AmpC, and carbapenemase-resistance genes were prevalent. A total of 130 (33.2%) patients died, predominantly those in the intensive-care unit undergoing mechanical ventilation or extracorporeal membrane oxygenation. Conclusion: Despite the low occurrence of coinfections among patients with COVID-19 in our setting, clinical outcomes remained poor. Predominance of Gram-negative pathogens, emergence of Candida species, and prevalence of isolates harboring drug-resistance genes are of concern

Healthcare derived Smart watches and mobile phones are contaminated niches to multidrug resistant and highly virulent microbes

Background: As high touch wearable devices, the potential for microbial contamination of smart watches is high. In this study, microbial contamination of smart watches of healthcare workers (HCWs) was assessed and compared to the individual’s mobile phone and hands. Methods: This study was part of a larger point prevalence survey of microbial contamination of mobile phones of HCWs at the emergency unit of a tertiary care facility. Swabs from smart watches, mobile phones and hands were obtained from four HCWs with dual ownership of these digital devices. Bacterial culture was carried out for all samples and those from smart watches and mobile phones were further assessed using shotgun metagenomic sequencing. Results: Majority of the participants were females (n/N = 3/4; 75%). Although they all use their digital devices at work and believe that these devices could harbour microbes, cleaning in the preceding 24 hours was reported by one individual. Predominant organisms identified on bacterial culture were multidrug resistant Staphylococcus hominis and Staphylococcus epidermidis. At least one organism identified from the hands was also detected on all mobile phones and two smart watches. Shotgun metagenomics analysis demonstrated greater microbial number and diversity on mobile phones compared to smart watches. All devices had high signatures of Pseudomonas aeruginosa and associated bacteriophages and antibiotic resistance genes. Almost half of the antibiotic resistance genes (n/N = 35/75;46.6%) were present on all devices and majority were related to efflux pumps. Of the 201 virulence factor genes (VFG) identified, majority (n/N = 148/201;73%) were associated with P. aeruginosa with 96% (n/N = 142/148) present on smart watches and mobile phones. Conclusion: This first report on microbial contamination of smart watches using metagenomics next generation sequencing showed similar pattern of contamination with microbes, VFG and antibiotic resistance genes across digital devices. Further studies on microbial contamination of wearable digital devices are urgently needed

Gut microbiota interplay with COVID-19 reveals links to host lipid metabolism among Middle Eastern populations

The interplay between the compositional changes in the gastrointestinal microbiome, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) susceptibility and severity, and host functions is complex and yet to be fully understood. This study performed 16S rRNA gene-based microbial profiling of 143 subjects. We observed structural and compositional alterations in the gut microbiota of the SARS-CoV-2-infected group in comparison to non-infected controls. The gut microbiota composition of the SARS-CoV-2-infected individuals showed an increase in anti-inflammatory bacteria such as Faecalibacterium (p-value = 1.72 × 10–6) and Bacteroides (p-value = 5.67 × 10–8). We also revealed a higher relative abundance of the highly beneficial butyrate producers such as Anaerostipes (p-value = 1.75 × 10–230), Lachnospiraceae (p-value = 7.14 × 10–65), and Blautia (p-value = 9.22 × 10–18) in the SARS-CoV-2-infected group in comparison to the control group. Moreover, phylogenetic investigation of communities by reconstructing unobserved state (PICRUSt) functional prediction analysis of the 16S rRNA gene abundance data showed substantial differences in the enrichment of metabolic pathways such as lipid, amino acid, carbohydrate, and xenobiotic metabolism, in comparison between both groups. We discovered an enrichment of linoleic acid, ether lipid, glycerolipid, and glycerophospholipid metabolism in the SARS-CoV-2-infected group, suggesting a link to SARS-CoV-2 entry and replication in host cells. We estimate the major contributing genera to the four pathways to be Parabacteroides, Streptococcus, Dorea, and Blautia, respectively. The identified differences provide a new insight to enrich our understanding of SARS-CoV-2-related changes in gut microbiota, their metabolic capabilities, and potential screening biomarkers linked to COVID-19 disease severity